System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving an image of a passport; means for extracting characters from the received image of the passport as text data; means for translating the extracted text data; and means for reviewing the translated text data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When foreigners sign up for mobile phone contracts or other services, if the foreign passports they submit as identification are written in a language other than English, there is a problem of difficulty in deciphering and screening them. This is particularly true when there is no embassy in the country or when there is a risk of fraudulent applications, which reduces the quality and reliability of the screening process. To solve this problem, there is a need for a highly accurate and efficient method of verifying and screening the contents of foreign language passports. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system that includes a means for receiving a passport image, a means for extracting characters from the received passport image as text data, a means for translating the extracted text data, and a means for reviewing the translated text data. This system extracts text information from the passport image using AI-OCR, translates it with high accuracy, and then compares it with the review standards to verify it. This allows the contents of foreign language passports to be accurately deciphered, enabling high-quality review.

[0006] "Passport image" refers to a digital copy of a passport, which is an identification document that foreigners submit when signing up for a mobile phone contract or other service.

[0007] "Means for receiving" refers to the function of receiving the image data of the passport acquired by the user using the terminal on the server side.

[0008] "Means of extracting characters as text data" refers to the function of using AI-based optical character recognition (OCR) technology to extract character information from passport images and convert it into digital text format.

[0009] "Means of translation" refers to the function of converting extracted text data into the desired language using generative AI or translation API.

[0010] "Means of review" refers to the comparison and verification function to confirm whether the translated text data meets the review criteria. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0012] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0015] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0016] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0017] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0019] [First embodiment]

[0020] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0021] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0024] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0027] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0031] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0032] System Overview

[0033] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones, etc., and translates and examines the contents. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the contents accurately.

[0034] System configuration

[0035] 1. Passport Image Capture Module

[0036] Users take a picture of their passport using their handheld device, which then uploads the image to the server.

[0037] 2. Receiving and OCR module

[0038] The server passes the received image file to the AI-OCR engine to extract text data from the image.

[0039] 3. Translation Module

[0040] The server uses the extracted text in a translation engine to translate it into the specified language.

[0041] 4. Review Module

[0042] The server then uses the translated text to verify necessary information such as passport number and name against the screening criteria.

[0043] 5. Log Management Module

[0044] The server logs all transaction results and stores audit data to ensure transaction traceability.

[0045] Program processing

[0046] Capture and upload a passport image

[0047] The user takes a photo of their passport using the device's camera and uploads it to a specified server URL. The device is equipped with a program that sends the captured image file to the server, thereby sending the image data in real time.

[0048] Extracting text data using OCR

[0049] The server processes the passport image it receives with an AI-OCR engine. The OCR engine automatically detects text information in the image and converts it into text data. For example, information such as passport number, name, and place of birth is converted into text.

[0050] Translation Processing

[0051] The server then passes the extracted text data to a translation engine for translation into a specific language. This uses common translation services such as Google Translate API to ensure fast and accurate translation.

[0052] Input data review

[0053] The server receives the translated text data and checks it against pre-defined criteria, such as whether the passport number or the applicant's name matches the data in the system. Based on the results of this check, it decides whether the application is approved or not.

[0054] Logging and Auditing

[0055] The server logs all processing steps in detail. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[0056] Specific examples

[0057] The user takes a photo of their passport on their device and uploads it to the server. At that time, the message displayed on the device is "Uploading image to server," and after the transfer is complete, the message "Upload completed" is displayed.

[0058] The server receives the image and extracts the text information from the passport through the OCR module. The log records "OCR processing completed. Extracted text will be displayed."

[0059] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[0060] The server reviews the translated text in the review module and confirms the result. The log will say "Review completed. Recording the result."

[0061] In this way, the present invention makes it possible to efficiently and accurately inspect passports written in foreign languages, thereby facilitating the smooth processing of contracts for mobile phones and other devices.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The user takes a picture of the passport using their device, activates the device's camera function, and takes a picture so that the entire passport is clearly visible. After checking the image, the user saves it on the device.

[0065] Step 2:

[0066] The device uploads the passport image it has taken to the specified server URL. The device sends the image file (e.g., passport.jpg) to the server using an HTTP POST request. During this process, the device displays the message "Sending image to server" to the user.

[0067] Step 3:

[0068] The server receives the uploaded image, temporarily stores the image data, and then proceeds to the next processing step.

[0069] Step 4:

[0070] The server passes the received passport image to the AI-OCR engine and extracts text information from the image. To do this, the image file is first read into the OCR engine and output as text data. The server log records "OCR processing completed."

[0071] Step 5:

[0072] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[0073] Step 6:

[0074] The server passes the translated text data to the review module for review. The server compares the translated text with pre-defined reference data to ensure that they match. For example, it verifies that the passport number and name match the reference data.

[0075] Step 7:

[0076] The server records the results of the review in a log. If necessary, it notifies the user of the results. The server's log records "The review has been completed. The results will be recorded." At this stage, the entire process is complete.

[0077] The above steps enable efficient processing of passports written in foreign languages ​​submitted by users and highly accurate screening, significantly improving the reliability and efficiency of contract procedures.

[0078] Example 1

[0079] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0080] Conventional passport inspection systems lack sufficient automation for character recognition and translation of passports written in foreign languages, resulting in time-consuming and labor-intensive processes. There was also room for improvement in the accuracy and efficiency of inspections. This created a growing need for a system that could quickly and accurately extract passport text data, automatically translate it, and inspect it. Furthermore, there was a need for detailed log management to ensure transparency and traceability of processing.

[0081] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0082] In this invention, the server includes a means for taking a passport image using a terminal and uploading it to the server, a means for processing the received passport image with an optical character recognition engine to extract characters as text data, a means for translating the extracted text data into a specified language using a translation engine, a means for comparing the translated text data with preset standards and reviewing it, and a means for recording all processing steps in detail in a log and saving it for audit purposes. This makes it possible to efficiently and accurately recognize, translate, and review passports written in foreign languages, thereby smoothly progressing contract procedures. Furthermore, log management ensures system transparency and traceability, improving reliability.

[0083] A "terminal" is an electronic device used by a user, such as a mobile phone, smartphone, or tablet, that has a camera function.

[0084] A "server" is a computer system that receives and processes data from terminals via a network, and analyzes and reviews it using various engines.

[0085] "Passport image" is a photograph of a travel document taken by a user with the camera on the terminal, and is image data used for various inspections.

[0086] An "optical character recognition engine (OCR engine)" is a general term for software that detects character information from image data and converts it into text data.

[0087] "Text data" is a data format that includes character information extracted by an OCR engine, and is the content of a document recognized as a string of characters.

[0088] A "translation engine" is software or a service for translating strings from one language to another.

[0089] "Criteria" are pre-defined evaluation criteria or conditions used when reviewing text data.

[0090] "Review" is the process of comparing the extracted and translated text data with standards to confirm matches.

[0091] A "log" is data that describes the work history and results recorded at each processing step of the system.

[0092] "Stored for audit" means storing processing history and results in a secure location for future verification and troubleshooting.

[0093] MODE FOR CARRYING OUT THE INVENTION

[0094] This invention relates to a system that analyzes passport images presented by foreigners, translates their contents, and examines them. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the data, enabling smooth contract procedures for mobile phones and other devices.

[0095] Hardware and Software Configuration

[0096] The hardware used includes a terminal (such as a smartphone or tablet) and a server. The terminal has a camera function that the user uses to take a passport image.

[0097] The software consists of the following:

[0098] 1. Passport Image Capture Module:

[0099] The user takes a picture of the passport using the device's camera and sends it to the server using a dedicated upload application.

[0100] 2. Receiving and OCR module:

[0101] The server saves the received image files in a specific folder and extracts the text information using an AI-OCR engine, such as the Google Cloud Vision API.

[0102] 3. Translation Module:

[0103] The server sends the text data generated by OCR to a translation engine (such as Google Translate API) and translates it into the specified language.

[0104] 4. Review Module:

[0105] The server reviews the translated text data against pre-set criteria and verifies necessary information such as passport number and name.

[0106] 5. Log Management Module:

[0107] The server will log all transaction results in detail and store audit data to ensure transaction traceability.

[0108] Specific examples

[0109] The user takes a photo of their passport on their device and sends it to the server using a dedicated upload application. The message displayed on the device is "Uploading image to server," and after sending is complete, the message "Upload completed" is displayed.

[0110] The server passes the received image file to the AI-OCR engine for processing. For example, it logs a message saying, "OCR processing completed. Extracted text displayed."

[0111] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[0112] The server evaluates the translated text in the review module and confirms the result. The log will say "Review completed. Recording result."

[0113] Prompt Sentence Examples

[0114] Here are some example prompts for the generative AI model:

[0115] 1. Prompt:

[0116] Upload passport images and create a program that uses AI-OCR and a translation engine to examine the contents of foreign passports.

[0117] 2. Examples of prompts:

[0118] Build a system that takes a photo of a foreigner's passport with a smartphone camera and uploads it to a server, which then extracts text using AI-OCR and translates it using the Google Translate API, and then automatically reviews the passport contents based on that.

[0119] In this way, by clearly specifying the specific processing steps and the hardware and software to be used, it is possible to provide a system that can efficiently process passport contents written in a foreign language and carry out contract procedures smoothly.

[0120] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0121] Program processing flow

[0122] Step 1: Capture and upload a passport image

[0123] Input: Passport image taken by the user using the device camera

[0124] Output: Image file uploaded to the server

[0125] 1. The user launches the camera application on the device.

[0126] 2. The user uses the camera application to take an image containing the entire passport.

[0127] 3. The device displays an interface for uploading the captured images to the server using a dedicated application.

[0128] 4. The user taps the "Upload image" button, and the device sends the image file to the specified server URL. For example, a message appears saying "Uploading image to server."

[0129] 5. Once the image upload is complete, the device will display "Upload complete."

[0130] Step 2: Receiving images and extracting text data using OCR

[0131] Input: Passport image file uploaded to the server

[0132] Output: Text data extracted by OCR

[0133] 1. The server saves the uploaded image files in a specific folder.

[0134] 2. The server passes the saved image file to the AI-OCR engine, which uses the Google Cloud Vision API or similar.

[0135] 3. The AI-OCR engine analyzes the text information in the image and extracts text data such as passport number, name, and place of birth.

[0136] 4. The server temporarily stores the extracted text data in an internal database.

[0137] 5. The processing log will record "OCR processing completed. Extracted text: [Extracted text]".

[0138] Step 3: Translating the text data

[0139] Input: Text data extracted by OCR

[0140] Output: Text data translated by the translation engine

[0141] 1. The server reads the temporarily stored text data and connects to a translation engine (such as Google Translate API).

[0142] 2. The server passes the text data to the translation engine and requests translation into the specified language.

[0143] 3. The translation engine translates the text data into the specified language and returns the translated text data to the server.

[0144] 4. The server receives the translation results and stores them in memory or a database.

[0145] 5. Record the following in the processing log: "Text translation completed. Translation result: [translated text]."

[0146] Step 4: Translation review

[0147] Input: Translated text data

[0148] Output: Review results

[0149] 1. The server reads the pre-defined review criteria from the database.

[0150] 2. The server compares the translation data with the review criteria and confirms a match.

[0151] 3. For example, checking that translated passport numbers are in a valid format and names follow a specific format.

[0152] 4. The server generates the review results and records them in the database.

[0153] 5. Record "Review completed. Result: [Review result]" in the processing log.

[0154] Step 5: Log Management and Auditing

[0155] Input: Execution results and status data for each processing step

[0156] Output: Detailed log files and audit data

[0157] 1. The server records all processing results and times in a log file for each step of image reception, OCR processing, translation processing, and review.

[0158] 2. The server stores the status (success / failure) and detailed error message for each operation.

[0159] 3. The server will regularly back up audit log data and store it in secure storage.

[0160] 4. The server uses these logs for future audits and troubleshooting.

[0161] 5. Record "Log management and audit data storage completed" in the processing log.

[0162] This enables the system to efficiently and accurately analyze passports written in foreign languages, facilitating smooth contract procedures.

[0163] (Application example 1)

[0164] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0165] Conventional identity verification systems using passport information have difficulty handling passports written in multiple languages, making accurate identity verification difficult. Furthermore, because real-time processing was not possible, the verification process took time, resulting in poor user convenience. Furthermore, the lack of traceability and transparency in the process made auditing and troubleshooting difficult.

[0166] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0167] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for reviewing the translated text data, means for taking a passport image with a smart device and processing it in real time, means for verifying the identity of the person by comparing the translated text data with the reservation system, and means for recording all processing steps in a log. This enables accurate real-time identity verification in multiple languages, improving user convenience. It also ensures traceability and transparency of the process, facilitating audits and troubleshooting.

[0168] The "means for receiving a passport image" is a combination of hardware and software that allows a user to take an image of their passport and send the image data to a server.

[0169] The "means for extracting characters from a received passport image as text data" is a system that includes a process of analyzing a received passport image, extracting character information using optical character recognition technology, and converting it into text data.

[0170] "Means for translating extracted text data" refers to software and algorithms for translating the text data extracted by optical character recognition technology into another specified language, such as by using an online translation service or a translation API.

[0171] The "means for reviewing translated text data" refers to a system that structures translated text data and reviews it by comparing it with pre-established standards or databases.

[0172] "Means for taking passport images using a smart device and processing them in real time" refers to hardware and software that allows a passport image to be taken using a mobile device such as a smartphone or tablet, and then immediately sends the image to a server to begin analysis.

[0173] "Means for verifying identity by comparing translated text data with the reservation system" refers to a system that compares translated passport information with the database of the existing reservation system to confirm a match and verify that the user is a legitimate person making a reservation.

[0174] "Means for logging all processing steps" refers to a system that records in detail all processing steps, including receipt, OCR processing, translation, and review, and saves the log data. This ensures traceability and transparency of the process.

[0175] MODE FOR CARRYING OUT THE INVENTION

[0176] The following describes in detail the mode for carrying out this invention. This system is designed to verify the identity of foreign tourists using passport information when they use an automated driving vehicle. The system is composed of the following main components:

[0177] Key Elements

[0178] 1. Passport image capture function

[0179] The user takes a photo of the passport using a smart device (smartphone, tablet, etc.), and the image is uploaded to the server as is.

[0180] 2. Real-time OCR processing

[0181] The server processes the received passport image using an optical character recognition (OCR) engine (e.g., Tesseract OCR) and converts the character information in the image into text data.

[0182] 3. Real-time translation function

[0183] The server translates the text data extracted by OCR into the specified language using an automatic translation engine (e.g., Google Translate API).

[0184] 4. Identity Verification

[0185] The server compares the translated text data with the data in the reservation system to verify that the user is a legitimate user.

[0186] 5. Data log management

[0187] The server logs all processing steps in detail and stores audit data to ensure traceability and transparency of the process.

[0188] Hardware and Software Configuration

[0189] The specific hardware and software used are shown below.

[0190] Smart Devices

[0191] Users take a passport photo using a smart device (smartphone or tablet) and upload the image to the server.

[0192] server

[0193] The following software is installed on the server:

[0194] Optical Character Recognition Engine: Tesseract OCR

[0195] Machine translation engine: Google Translate API

[0196] Database system: SQLite or other database system

[0197] Log management software: ElasticSearch, etc.

[0198] Example of operation

[0199] As an example, consider a scenario where a foreign tourist boards an autonomous vehicle. The tourist uses a smart device to take a photo of their passport. The image data is sent to a server in real time and converted into text data using OCR technology. The text data is translated using the Google Translate API and matched with data from the reservation system. Finally, all processing steps are logged to enable future audits and troubleshooting.

[0200] Example prompt sentence:

[0201] Passport authentication process in autonomous vehicle boarding verification system:

[0202] 1. Travelers capture a passport image with their smartphone.

[0203] 2. Extract text data from images using an OCR engine.

[0204] 3. Translate the extracted text into Japanese using the Google Translate API.

[0205] 4. The translation results are compared with the ride reservation information.

[0206] example:

[0207] Take a picture of your passport and start the OCR process. The process is complete. Your passport information has been converted to text.

[0208] The OCR extracted text was then translated to "Hello." The translated text was then matched against the reservation system to verify the identity of the person.

[0209] In this way, this invention will streamline the identity verification process for foreign tourists when using self-driving vehicles, enabling accurate verification in real time.

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] The user takes a picture of their passport with a smart device (smartphone or tablet) and obtains the image data. Specifically, the user launches the camera app and takes a picture of the passport. The input is the image of the passport taken by the user, and the output is the image data.

[0213] Step 2:

[0214] The terminal uploads the acquired passport image to the server. The terminal has a built-in program that sends the captured image to a specified server URL, which sends the image data to the server in real time. The input is the passport image data, and the output is the image data sent to the server.

[0215] Step 3:

[0216] The server inputs the received passport image into an optical character recognition (OCR) engine to extract text information from the image. Specifically, it uses Tesseract OCR to convert the text information in the image into text data. The input is the passport image data, and the output is the extracted text data.

[0217] Step 4:

[0218] The server passes the text data extracted by OCR to the translation engine and translates it into the specified language. Specifically, the text data is translated using the Google Translate API. The input is the text data extracted by OCR, and the output is the translated text data.

[0219] Step 5:

[0220] The server checks the translated text against the reservation system to verify that the user is a valid reservation holder. Specifically, it performs a database query to verify a match against the reservation information. The input is the translated text and the reservation system data, and the output is the identity verification result.

[0221] Step 6:

[0222] The server records all processing steps in a log and saves the audit data. Specifically, it records the details of the processing performed at each step and the results, and saves them in log management software such as ElasticSearch. The input is the result data of each processing step, and the output is the saved log data.

[0223] This processing flow automates the entire process, from taking passport photos to identity verification and log management, ensuring smooth identity verification for foreign tourists when using self-driving vehicles.

[0224] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0225] System Overview

[0226] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones and other devices, translates the contents, and reviews them. It also combines an emotion engine that recognizes the user's emotions. This system converts passport images taken by users into text data using AI-OCR technology, which then translates the data for accurate review. It also recognizes the user's emotions, records the user's emotional state during the review process, and provides feedback as needed.

[0227] System configuration

[0228] 1. Passport Image Capture Module

[0229] The user takes a photo of their passport using their handheld device. The device also uses a camera and microphone to capture the image and to recognize the user's emotions. This data is then uploaded to the server.

[0230] 2. Receiving and OCR module

[0231] The server processes the received image file and emotion data, and uses an AI-OCR engine to extract text data from the passport image.

[0232] 3. Translation Module

[0233] The server passes the extracted text to a translation engine for translation into a specific language, while simultaneously analyzing the user's emotional data and recording the user's emotional state during the review process.

[0234] 4. Review Module

[0235] The server then compares the translated text with the necessary information, such as passport number and name, to verify it against the screening criteria. Furthermore, an emotion engine evaluates the user's emotional state and provides feedback to ensure the fairness of the screening process and the user's sense of security.

[0236] 5. Log Management Module

[0237] The server logs all processing results and emotion data and stores audit data to ensure processing traceability.

[0238] Program processing

[0239] Capture and upload a passport image

[0240] The user takes a passport photo with the device's camera and records their own face and voice to obtain emotion data, which is then uploaded to the server.

[0241] Extracting text data using OCR

[0242] The server processes the received passport image with an AI-OCR engine, extracts text information from the image, and simultaneously analyzes the received emotional data to obtain the user's emotional state. For example, it determines whether the user is relaxed or anxious.

[0243] Translation processing and sentiment analysis

[0244] The server passes the text data extracted by OCR to a translation engine, which translates it into the specified language (e.g., English). In parallel, the emotion engine analyzes the user's emotion data and detects significant emotional changes.

[0245] Review and feedback of input data

[0246] The server then checks the translated text against pre-defined criteria. To ensure fairness in the review, the system also evaluates the user's emotional state and provides appropriate feedback. For example, if the user is feeling anxious, the system can send a reassuring message.

[0247] Logging and Auditing

[0248] The server records detailed logs of all processing steps and the corresponding emotion data. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[0249] Specific examples

[0250] The user takes a photo of their passport on their device and uploads it to the server, while simultaneously capturing a photo of their face to obtain emotional data. The device displays "Uploading image to server," and once the upload is complete, it displays "Upload completed."

[0251] The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and simultaneously performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[0252] The server uses a translation module to translate the extracted text and analyze the sentiment data to obtain insights necessary for review. The log records, "Text translation and sentiment analysis completed."

[0253] The server reviews the translated text and confirms the results while assessing the user's emotional state. It provides feedback to the user as needed. The log states, "Review completed. Recording results and feedback."

[0254] In this way, the present invention can efficiently process passport contents written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[0255] The processing flow will be explained below.

[0256] Step 1:

[0257] The user takes a picture of their passport using their device. The device's camera function is activated and the entire passport is captured clearly. At the same time, the user's face and voice are also recorded, and emotional data is acquired. This image and emotional data are then stored on the device.

[0258] Step 2:

[0259] The device uploads the passport image and emotion data it has taken to the specified server URL. The device then sends the image file (e.g., passport.jpg) and emotion data to the server using an HTTP POST request. During this process, the device displays a message to the user saying, "Sending image and emotion data to server."

[0260] Step 3:

[0261] The server receives the uploaded image and emotion data. The server temporarily stores this data and proceeds to the next processing step. The server log records "Passport image and emotion data received."

[0262] Step 4:

[0263] The server passes the received passport image to the AI-OCR engine, which extracts text information from the image. The OCR engine analyzes the image file and outputs it as text data. At the same time, the emotion engine analyzes the received emotion data. The server log records, "OCR processing and emotion analysis completed."

[0264] Step 5:

[0265] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[0266] Step 6:

[0267] The server obtains the text data translated by the translation engine and passes it to the review module. The review module compares the translated text with pre-set reference data to confirm whether they match. At the same time, it evaluates the emotional data analyzed by the emotion engine to ensure the fairness of the review process. The server log records "Review and emotion evaluation completed."

[0268] Step 7:

[0269] The server provides feedback to the user based on the review results and emotional data. For example, if the user is feeling anxious, it will send a reassuring message. The user can check the results and feedback on their device. The server log will record "Feedback has been sent to the user."

[0270] Step 8:

[0271] The server records all processing results and emotion data in a detailed log and saves it as audit data. This log is used for future review and troubleshooting. The server log will record "All processing has been logged."

[0272] This series of steps allows for efficient processing of passports submitted by users written in foreign languages ​​and highly accurate screening. Furthermore, by using an emotion engine, a fair screening process is realized that takes into account the user's emotional state. This significantly improves the reliability and efficiency of contract procedures.

[0273] Example 2

[0274] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0275] When foreigners apply for a contract for a mobile phone or other device, the details of their passport must be accurately analyzed and reviewed. However, it is difficult to process passport details written in a foreign language quickly and accurately. Furthermore, there is a lack of a system to alleviate the anxiety and stress users may feel during the process. Furthermore, traceable log management is necessary to ensure the fairness and transparency of the process.

[0276] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for acquiring emotional data from the user, means for analyzing the acquired emotional data, means for reviewing the translated text data, means for providing feedback based on the review results and the emotional data, and means for recording the processing steps and the emotional data in a log. This enables a fair review process that takes into account the emotional state of the user while efficiently processing the contents of a passport written in a foreign language, and highly transparent log management.

[0277] The "means for receiving a passport image" is a function for transmitting image data of a passport taken by a user using a terminal to a server, and for the server to receive the image data.

[0278] The "means for extracting characters as text data from a received passport image" is a function that uses optical character recognition (OCR) technology to extract character information from a received passport image as digital text data.

[0279] The "means for translating extracted text data" is a function for converting text data extracted by OCR into a specified language using a multilingual translation engine.

[0280] The "means for acquiring emotional data from the user" is a function for detecting and acquiring the emotional state of the user using the user's facial image and voice data.

[0281] The "means for analyzing acquired emotional data" is a function for analyzing acquired emotional data and grasping the emotions (relaxation, tension, anxiety, etc.) that the user is experiencing.

[0282] The "means for reviewing translated text data" refers to a function for comparing the translated text data with pre-established review criteria to confirm its accuracy and suitability.

[0283] "Means for providing feedback based on the screening results and emotional data" is a function that provides appropriate feedback to the user (such as a message that gives a sense of security or instructions on the next steps) based on the screening results and emotional data.

[0284] The "means for logging processing steps and emotional data" refers to a function that records all processing steps and the corresponding emotional data in detail as a log and saves it for future audits and troubleshooting.

[0285] The present invention is a system used by foreigners when completing procedures such as signing a mobile phone contract, and combines passport image analysis, translation, and user emotion recognition. Details for implementing this system are described below.

[0286] System configuration

[0287] 1. Passport Image Capture Module

[0288] The user takes a photo of their passport using the camera on their device. The system also captures emotional data, such as the user's face and voice, which are then encoded and uploaded to the server.

[0289] 2. Receiving and OCR module

[0290] The server receives the passport image and emotion data sent by the user. It then uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text data from the received passport image. In parallel, the emotion data is also analyzed to understand the user's emotional state.

[0291] 3. Translation Module

[0292] The server passes the text data extracted by the AI-OCR engine to a translation engine (e.g., Google Translate API) and translates it into the specified language (e.g., English). At the same time, it also uses an emotion engine to analyze emotion data and records changes in the user's emotional state.

[0293] 4. Review Module

[0294] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, issue date, expiration date, etc.) to verify accuracy and consistency. Furthermore, it evaluates the emotional data analyzed by the emotion engine and provides feedback to the user to maintain a fair review process.

[0295] 5. Log Management Module

[0296] The server records and stores detailed logs of all processing steps and the corresponding emotion data, ensuring transparency and traceability of the system and allowing for future review and troubleshooting.

[0297] Example

[0298] 1. The user takes a photo of their passport on their device and uploads it to the server, while simultaneously recording their facial image and voice to obtain emotional data. The device displays "Uploading image to server" and notifies them that "Upload completed" when the upload is complete.

[0299] 2. The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[0300] 3. The server uses the translation module to translate the extracted text and analyze the sentiment data to obtain insights needed for review. The log records, "Text translation and sentiment analysis completed."

[0301] 4. The server reviews the translated text, assesses the user's emotional state, and confirms the results. It provides feedback to the user if necessary. The log records, "Review completed. Feedback has been sent to the user."

[0302] 5. The server records all processing steps and emotion data in a detailed log and stores it for future auditing. The log will state, "All processing steps completed. Log data stored."

[0303] Prompt Sentence Examples

[0304] The following prompt sentences can be input to the generative AI model:

[0305] "Please build a system that analyzes an image of my passport, translates and reviews the contents, and simultaneously assesses my emotional state. Please explain the specific steps and technologies used."

[0306] In this way, the embodiments of the invention effectively process the contents of passports written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[0307] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0308] Step 1: Taking a passport photo and acquiring emotion data

[0309] The user takes a passport image using the camera on their device. At the same time, emotional data such as their face and voice are captured. Specifically, the user captures this data by pressing the capture button using a camera and microphone with facial recognition capabilities. The device encodes this data and uploads it to the server. The input is the image captured by the device camera and the recorded voice data, and the output is a data packet containing these uploaded to the server.

[0310] Step 2: Receiving and storing data

[0311] The server receives data packets sent by the user. The server stores the passport image file and emotion data (face image and voice data) in its respective data storage. The input is a data packet containing the image and emotion data from the user terminal, and the output is the passport image file and emotion data stored in the data storage.

[0312] Step 3: Extract text data using OCR

[0313] The server inputs the saved passport image into an AI-OCR engine (for example, Google Cloud Vision API) and extracts text information from the image. Specifically, the passport image data is passed to the engine, and text data such as the name and passport number is extracted from it. The input is the saved passport image file, and the output is the extracted text data.

[0314] Step 4: Analyze the sentiment data

[0315] The server inputs the stored facial image and voice data into an emotion engine to analyze the user's emotional state. Specifically, it uses facial expression recognition and voice analysis technology to evaluate the user's emotions, such as whether they are relaxed or anxious. The input is the stored facial image and voice data, and the output is the analyzed emotional state data.

[0316] Step 5: Translating the text data

[0317] The server passes the text data extracted by OCR to a translation engine (e.g., Google Translate API) to translate it into the specified language. For example, translating Japanese text into English. The input is the extracted text data, and the output is the translated text data.

[0318] Step 6: Review and evaluate the translation data

[0319] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, expiration date, etc.) to verify its accuracy and suitability. At the same time, it evaluates the emotion data to ensure that the review is fair. The input is the translated text data and the analyzed emotion data, and the output is the review result.

[0320] Step 7: Provide feedback to users

[0321] The server provides appropriate feedback to the user based on the evaluation result and emotion data. For example, if the user feels anxious, it sends a message such as "Everything is fine. Don't worry." The input is the evaluation result and emotion data, and the output is the feedback message sent to the user.

[0322] Step 8: Logging and Auditing

[0323] The server records and stores detailed logs of all processing steps and corresponding emotion data for later review and troubleshooting. The inputs are each processing step and its output data, and the output is the stored log data.

[0324] (Application example 2)

[0325] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0326] It is difficult to efficiently and accurately verify the identity of foreign users of self-driving vehicles, and there are also lack of measures to alleviate anxiety caused by language differences and cultural backgrounds. Therefore, it is necessary to provide a sense of security to foreign users in self-driving vehicles by quickly and accurately authenticating them and at the same time taking into account their emotional state.

[0327] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0328] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for examining the translated text data, an emotion engine for recognizing a user's emotion, means for recording the user's emotional state and providing feedback as necessary, and means for processing passport recognition and the user's emotional state within the self-driving vehicle. This makes it possible to quickly and accurately verify the identity of foreign users of self-driving vehicles and provide feedback according to their emotional state.

[0329] "Means for receiving a passport image" refers to a device or method that has the function of taking or scanning an image of the passport presented by the user and transmitting it to the system.

[0330] The "means for extracting characters as text data" refers to a device or method that has the function of recognizing character information from a received passport image and converting it into digital text data.

[0331] The "means for translating extracted text data" refers to a device or method that has the function of translating text data obtained by OCR (Optical Character Recognition) into a different language.

[0332] "Means for reviewing translated text data" means a device or method that has the function of checking and verifying translated text data against pre-established criteria.

[0333] An "emotion engine that recognizes the user's emotions" is a device or software that has the function of analyzing the user's facial expressions, voice, etc. and determining their emotional state.

[0334] A "means for recording a user's emotional state and providing feedback as needed" is a device or method capable of recording a user's emotional state and providing reassuring messages or other feedback based on that data.

[0335] "Means for recognizing passports and processing the emotional state of users within an autonomous vehicle" refers to a device or method that is a system installed in an autonomous vehicle and has the function of recognizing the passport information of foreign users and analyzing the emotional state of the users to respond appropriately.

[0336] MODE FOR CARRYING OUT THE INVENTION

[0337] System configuration

[0338] This invention is a system for efficiently and accurately implementing passport-based authentication procedures for foreign users in automated driving vehicles. The system is composed of the following main components:

[0339] 1. Passport Image Capture Module

[0340] When a user gets into an autonomous vehicle, the device uses a camera installed inside the vehicle to take an image of the user's passport, and also captures video of the user's face to obtain emotional data.

[0341] 2. Data transmission module

[0342] The device transmits the acquired passport image and emotion data to a server via an internet connection.

[0343] 3. OCR and Translation Module

[0344] The server processes the received passport image using an AI-OCR engine to extract text information from the image, and then passes the extracted text data to a translation engine (e.g., Google Translate) to translate it into a specific language.

[0345] 4. Sentiment Analysis Module

[0346] The server analyzes the received emotion data and determines the user's emotional state using software such as the Facial Recognition Library.

[0347] 5. Review and Feedback Module

[0348] The server then authenticates the user based on the translated text data, comparing it with pre-defined criteria, while simultaneously recording the user's emotional state and sending reassuring feedback to the device as needed.

[0349] Program processing

[0350] The processing of each module is carried out as follows.

[0351] Passport image capture: The device takes a passport image using the in-car camera and simultaneously captures a video of the user's face. This data is temporarily stored on the device.

[0352] Data transmission: The device transmits the stored passport image and facial video to a server via the Internet.

[0353] OCR and translation: The server uses OpenCV and Pytesseract to perform OCR on the received passport image and extract text data, which is then translated into the specified language using the Google Translate API.

[0354] Emotion Analysis: The server analyzes the captured facial video using the Facial Recognition Library to determine the user's emotional state. This data is used as key insight into the review process.

[0355] Verification and feedback: The server performs authentication based on the translated text data, comparing it with pre-defined criteria. Depending on the user's emotional state, it sends appropriate feedback messages (e.g., "The process is going smoothly" or "Don't worry, please wait a moment for the process") to the terminal and displays them to the user.

[0356] Specific examples

[0357] As a concrete example, consider the following scenario.

[0358] 1. A user enters an autonomous vehicle and takes a photo of their passport using the device. The device displays "Sending image."

[0359] 2. The device sends the passport image and facial video to the server.

[0360] 3. The server processes the images with OCR, translates the text data, and analyzes the emotions in the facial images.

[0361] 4. The server judges the results of the evaluation and sends feedback to the device according to the user's emotional state.

[0362] 5. The device will display "The process is going smoothly" or "Don't worry, the process will take a moment."

[0363] Example prompt for a generative AI model:

[0364] The user takes a photo of their passport on the tablet and the message "Sending image" appears. The server then processes the image with OCR, translates it, and performs sentiment analysis, displaying feedback based on the user's emotional state. For example, "The process is going smoothly" or "Don't worry, please wait a moment while the process is completed."

[0365] In this way, the present invention makes it possible to quickly and accurately verify the identity of foreign users in self-driving vehicles and provide appropriate feedback according to their emotional state.

[0366] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0367] Program processing steps

[0368] Step 1:

[0369] The device is a camera installed in an autonomous vehicle that captures the user's passport image and facial video. The input is the passport image and the user's facial video, which are temporarily stored on the device. Specifically, the device's camera app is launched, the user is instructed to show their passport, and the image is taken by pressing the shutter button.

[0370] Step 2:

[0371] The device sends the captured passport image and facial video to the server. The input is the passport image and facial video stored on the device, and the output is data sent over the Internet. Specifically, the device's network module is used to send an HTTP POST request to the specified server URL.

[0372] Step 3:

[0373] The server extracts text data from the received passport image using an AI-OCR engine. The input is the passport image, and the output is the extracted text data. Specifically, the image is read using OpenCV, and text information is extracted from the image using Pytesseract.

[0374] Step 4:

[0375] The server passes the extracted text data to a translation engine for translation into a specific language. The input is OCR-processed text data, and the output is translated text data. Specifically, the text data is sent to the Google Translate API and the translated results are received.

[0376] Step 5:

[0377] The server analyzes the received facial video using an emotion analysis module to determine the user's emotional state. The input is the user's facial video, and the output is the analyzed emotional data. Specifically, the server processes the facial video using the Facial Recognition Library and classifies the emotional state.

[0378] Step 6:

[0379] The server compares the translated text data with the authentication criteria to confirm a match. At the same time, it records the user's emotional state and sends feedback as needed. The input is the translated text data and emotional data, and the output is the authentication result and a feedback message based on the emotion. Specifically, it compares the data with a pre-configured authentication criteria database to verify whether the user meets the authentication criteria, and generates a feedback message along with the authentication result.

[0380] Step 7:

[0381] The terminal displays the feedback message received from the server. The input is the feedback message sent from the server, and the output is the message displayed on the terminal display. As a specific operation, the message is displayed using a UI component that displays the message on the terminal display.

[0382] Through these processing steps, the system can quickly and accurately verify the identity of foreign users in autonomous vehicles and provide appropriate feedback according to their emotional state.

[0383] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0384] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0385] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0386] [Second embodiment]

[0387] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0388] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0389] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0390] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0391] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0392] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0393] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0394] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0395] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0396] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0397] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0398] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0399] System Overview

[0400] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones, etc., and translates and examines the contents. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the contents accurately.

[0401] System configuration

[0402] 1. Passport Image Capture Module

[0403] Users take a picture of their passport using their handheld device, which then uploads the image to the server.

[0404] 2. Receiving and OCR module

[0405] The server passes the received image file to the AI-OCR engine to extract text data from the image.

[0406] 3. Translation Module

[0407] The server uses the extracted text in a translation engine to translate it into the specified language.

[0408] 4. Review Module

[0409] The server then uses the translated text to verify necessary information such as passport number and name against the screening criteria.

[0410] 5. Log Management Module

[0411] The server logs all transaction results and stores audit data to ensure transaction traceability.

[0412] Program processing

[0413] Capture and upload a passport image

[0414] The user takes a photo of their passport using the device's camera and uploads it to a specified server URL. The device is equipped with a program that sends the captured image file to the server, thereby sending the image data in real time.

[0415] Extracting text data using OCR

[0416] The server processes the passport image it receives with an AI-OCR engine. The OCR engine automatically detects text information in the image and converts it into text data. For example, information such as passport number, name, and place of birth is converted into text.

[0417] Translation Processing

[0418] The server then passes the extracted text data to a translation engine for translation into a specific language. This uses common translation services such as Google Translate API to ensure fast and accurate translation.

[0419] Input data review

[0420] The server receives the translated text data and checks it against pre-defined criteria, such as whether the passport number or the applicant's name matches the data in the system. Based on the results of this check, it decides whether the application is approved or not.

[0421] Logging and Auditing

[0422] The server logs all processing steps in detail. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[0423] Specific examples

[0424] The user takes a photo of their passport on their device and uploads it to the server. At that time, the message displayed on the device is "Uploading image to server," and after the transfer is complete, the message "Upload completed" is displayed.

[0425] The server receives the image and extracts the text information from the passport through the OCR module. The log records "OCR processing completed. Extracted text will be displayed."

[0426] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[0427] The server reviews the translated text in the review module and confirms the result. The log will say "Review completed. Recording the result."

[0428] In this way, the present invention makes it possible to efficiently and accurately inspect passports written in foreign languages, thereby facilitating the smooth processing of contracts for mobile phones and other devices.

[0429] The processing flow will be explained below.

[0430] Step 1:

[0431] The user takes a picture of the passport using their device, activates the device's camera function, and takes a picture so that the entire passport is clearly visible. After checking the image, the user saves it on the device.

[0432] Step 2:

[0433] The device uploads the passport image it has taken to the specified server URL. The device sends the image file (e.g., passport.jpg) to the server using an HTTP POST request. During this process, the device displays the message "Sending image to server" to the user.

[0434] Step 3:

[0435] The server receives the uploaded image, temporarily stores the image data, and then proceeds to the next processing step.

[0436] Step 4:

[0437] The server passes the received passport image to the AI-OCR engine and extracts text information from the image. To do this, the image file is first read into the OCR engine and output as text data. The server log records "OCR processing completed."

[0438] Step 5:

[0439] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[0440] Step 6:

[0441] The server passes the translated text data to the review module for review. The server compares the translated text with pre-defined reference data to ensure that they match. For example, it verifies that the passport number and name match the reference data.

[0442] Step 7:

[0443] The server records the results of the review in a log. If necessary, it notifies the user of the results. The server's log records "The review has been completed. The results will be recorded." At this stage, the entire process is complete.

[0444] The above steps enable efficient processing of passports written in foreign languages ​​submitted by users and highly accurate screening, significantly improving the reliability and efficiency of contract procedures.

[0445] Example 1

[0446] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0447] Conventional passport inspection systems lack sufficient automation for character recognition and translation of passports written in foreign languages, resulting in time-consuming and labor-intensive processes. There was also room for improvement in the accuracy and efficiency of inspections. This created a growing need for a system that could quickly and accurately extract passport text data, automatically translate it, and inspect it. Furthermore, there was a need for detailed log management to ensure transparency and traceability of processing.

[0448] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0449] In this invention, the server includes a means for taking a passport image using a terminal and uploading it to the server, a means for processing the received passport image with an optical character recognition engine to extract characters as text data, a means for translating the extracted text data into a specified language using a translation engine, a means for comparing the translated text data with preset standards and reviewing it, and a means for recording all processing steps in detail in a log and saving it for audit purposes. This makes it possible to efficiently and accurately recognize, translate, and review passports written in foreign languages, thereby smoothly progressing contract procedures. Furthermore, log management ensures system transparency and traceability, improving reliability.

[0450] A "terminal" is an electronic device used by a user, such as a mobile phone, smartphone, or tablet, that has a camera function.

[0451] A "server" is a computer system that receives and processes data from terminals via a network, and analyzes and reviews it using various engines.

[0452] "Passport image" is a photograph of a travel document taken by a user with the camera on the terminal, and is image data used for various inspections.

[0453] An "optical character recognition engine (OCR engine)" is a general term for software that detects character information from image data and converts it into text data.

[0454] "Text data" is a data format that includes character information extracted by an OCR engine, and is the content of a document recognized as a string of characters.

[0455] A "translation engine" is software or a service for translating strings from one language to another.

[0456] "Criteria" are pre-defined evaluation criteria or conditions used when reviewing text data.

[0457] "Review" is the process of comparing the extracted and translated text data with standards to confirm matches.

[0458] A "log" is data that describes the work history and results recorded at each processing step of the system.

[0459] "Stored for audit" means storing processing history and results in a secure location for future verification and troubleshooting.

[0460] MODE FOR CARRYING OUT THE INVENTION

[0461] This invention relates to a system that analyzes passport images presented by foreigners, translates their contents, and examines them. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the data, enabling smooth contract procedures for mobile phones and other devices.

[0462] Hardware and Software Configuration

[0463] The hardware used includes a terminal (such as a smartphone or tablet) and a server. The terminal has a camera function that the user uses to take a passport image.

[0464] The software consists of the following:

[0465] 1. Passport Image Capture Module:

[0466] The user takes a picture of the passport using the device's camera and sends it to the server using a dedicated upload application.

[0467] 2. Receiving and OCR module:

[0468] The server saves the received image files in a specific folder and extracts the text information using an AI-OCR engine, such as the Google Cloud Vision API.

[0469] 3. Translation Module:

[0470] The server sends the text data generated by OCR to a translation engine (such as Google Translate API) and translates it into the specified language.

[0471] 4. Review Module:

[0472] The server reviews the translated text data against pre-set criteria and verifies necessary information such as passport number and name.

[0473] 5. Log Management Module:

[0474] The server will log all transaction results in detail and store audit data to ensure transaction traceability.

[0475] Specific examples

[0476] The user takes a photo of their passport on their device and sends it to the server using a dedicated upload application. The message displayed on the device is "Uploading image to server," and after sending is complete, the message "Upload completed" is displayed.

[0477] The server passes the received image file to the AI-OCR engine for processing. For example, it logs a message saying, "OCR processing completed. Extracted text displayed."

[0478] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[0479] The server evaluates the translated text in the review module and confirms the result. The log will say "Review completed. Recording result."

[0480] Prompt Sentence Examples

[0481] Here are some example prompts for the generative AI model:

[0482] 1. Prompt:

[0483] Upload passport images and create a program that uses AI-OCR and a translation engine to examine the contents of foreign passports.

[0484] 2. Examples of prompts:

[0485] Build a system that takes a photo of a foreigner's passport with a smartphone camera and uploads it to a server, which then extracts text using AI-OCR and translates it using the Google Translate API, and then automatically reviews the passport contents based on that.

[0486] In this way, by clearly specifying the specific processing steps and the hardware and software to be used, it is possible to provide a system that can efficiently process passport contents written in a foreign language and carry out contract procedures smoothly.

[0487] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0488] Program processing flow

[0489] Step 1: Capture and upload a passport image

[0490] Input: Passport image taken by the user using the device camera

[0491] Output: Image file uploaded to the server

[0492] 1. The user launches the camera application on the device.

[0493] 2. The user uses the camera application to take an image containing the entire passport.

[0494] 3. The device displays an interface for uploading the captured images to the server using a dedicated application.

[0495] 4. The user taps the "Upload image" button, and the device sends the image file to the specified server URL. For example, a message appears saying "Uploading image to server."

[0496] 5. Once the image upload is complete, the device will display "Upload complete."

[0497] Step 2: Receiving images and extracting text data using OCR

[0498] Input: Passport image file uploaded to the server

[0499] Output: Text data extracted by OCR

[0500] 1. The server saves the uploaded image files in a specific folder.

[0501] 2. The server passes the saved image file to the AI-OCR engine, which uses the Google Cloud Vision API or similar.

[0502] 3. The AI-OCR engine analyzes the text information in the image and extracts text data such as passport number, name, and place of birth.

[0503] 4. The server temporarily stores the extracted text data in an internal database.

[0504] 5. The processing log will record "OCR processing completed. Extracted text: [Extracted text]".

[0505] Step 3: Translating the text data

[0506] Input: Text data extracted by OCR

[0507] Output: Text data translated by the translation engine

[0508] 1. The server reads the temporarily stored text data and connects to a translation engine (such as Google Translate API).

[0509] 2. The server passes the text data to the translation engine and requests translation into the specified language.

[0510] 3. The translation engine translates the text data into the specified language and returns the translated text data to the server.

[0511] 4. The server receives the translation results and stores them in memory or a database.

[0512] 5. Record the following in the processing log: "Text translation completed. Translation result: [translated text]."

[0513] Step 4: Translation review

[0514] Input: Translated text data

[0515] Output: Review results

[0516] 1. The server reads the pre-defined review criteria from the database.

[0517] 2. The server compares the translation data with the review criteria and confirms a match.

[0518] 3. For example, checking that translated passport numbers are in a valid format and names follow a specific format.

[0519] 4. The server generates the review results and records them in the database.

[0520] 5. Record "Review completed. Result: [Review result]" in the processing log.

[0521] Step 5: Log Management and Auditing

[0522] Input: Execution results and status data for each processing step

[0523] Output: Detailed log files and audit data

[0524] 1. The server records all processing results and times in a log file for each step of image reception, OCR processing, translation processing, and review.

[0525] 2. The server stores the status (success / failure) and detailed error message for each operation.

[0526] 3. The server will regularly back up audit log data and store it in secure storage.

[0527] 4. The server uses these logs for future audits and troubleshooting.

[0528] 5. Record "Log management and audit data storage completed" in the processing log.

[0529] This enables the system to efficiently and accurately analyze passports written in foreign languages, facilitating smooth contract procedures.

[0530] (Application example 1)

[0531] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0532] Conventional identity verification systems using passport information have difficulty handling passports written in multiple languages, making accurate identity verification difficult. Furthermore, because real-time processing was not possible, the verification process took time, resulting in poor user convenience. Furthermore, the lack of traceability and transparency in the process made auditing and troubleshooting difficult.

[0533] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0534] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for reviewing the translated text data, means for taking a passport image with a smart device and processing it in real time, means for verifying the identity of the person by comparing the translated text data with the reservation system, and means for recording all processing steps in a log. This enables accurate real-time identity verification in multiple languages, improving user convenience. It also ensures traceability and transparency of the process, facilitating audits and troubleshooting.

[0535] The "means for receiving a passport image" is a combination of hardware and software that allows a user to take an image of their passport and send the image data to a server.

[0536] The "means for extracting characters from a received passport image as text data" is a system that includes a process of analyzing a received passport image, extracting character information using optical character recognition technology, and converting it into text data.

[0537] "Means for translating extracted text data" refers to software and algorithms for translating the text data extracted by optical character recognition technology into another specified language, such as by using an online translation service or a translation API.

[0538] The "means for reviewing translated text data" refers to a system that structures translated text data and reviews it by comparing it with pre-established standards or databases.

[0539] "Means for taking passport images using a smart device and processing them in real time" refers to hardware and software that allows a passport image to be taken using a mobile device such as a smartphone or tablet, and then immediately sends the image to a server to begin analysis.

[0540] "Means for verifying identity by comparing translated text data with the reservation system" refers to a system that compares translated passport information with the database of the existing reservation system to confirm a match and verify that the user is a legitimate person making a reservation.

[0541] "Means for logging all processing steps" refers to a system that records in detail all processing steps, including receipt, OCR processing, translation, and review, and saves the log data. This ensures traceability and transparency of the process.

[0542] MODE FOR CARRYING OUT THE INVENTION

[0543] The following describes in detail the mode for carrying out this invention. This system is designed to verify the identity of foreign tourists using passport information when they use an automated driving vehicle. The system is composed of the following main components:

[0544] Key Elements

[0545] 1. Passport image capture function

[0546] The user takes a photo of the passport using a smart device (smartphone, tablet, etc.), and the image is uploaded to the server as is.

[0547] 2. Real-time OCR processing

[0548] The server processes the received passport image using an optical character recognition (OCR) engine (e.g., Tesseract OCR) and converts the character information in the image into text data.

[0549] 3. Real-time translation function

[0550] The server translates the text data extracted by OCR into the specified language using an automatic translation engine (e.g., Google Translate API).

[0551] 4. Identity Verification

[0552] The server compares the translated text data with the data in the reservation system to verify that the user is a legitimate user.

[0553] 5. Data log management

[0554] The server logs all processing steps in detail and stores audit data to ensure traceability and transparency of the process.

[0555] Hardware and Software Configuration

[0556] The specific hardware and software used are shown below.

[0557] Smart Devices

[0558] Users take a passport photo using a smart device (smartphone or tablet) and upload the image to the server.

[0559] server

[0560] The following software is installed on the server:

[0561] Optical Character Recognition Engine: Tesseract OCR

[0562] Machine translation engine: Google Translate API

[0563] Database system: SQLite or other database system

[0564] Log management software: ElasticSearch, etc.

[0565] Example of operation

[0566] As an example, consider a scenario where a foreign tourist boards an autonomous vehicle. The tourist uses a smart device to take a photo of their passport. The image data is sent to a server in real time and converted into text data using OCR technology. The text data is translated using the Google Translate API and matched with data from the reservation system. Finally, all processing steps are logged to enable future audits and troubleshooting.

[0567] Example prompt sentence:

[0568] Passport authentication process in autonomous vehicle boarding verification system:

[0569] 1. Travelers capture a passport image with their smartphone.

[0570] 2. Extract text data from images using an OCR engine.

[0571] 3. Translate the extracted text into Japanese using the Google Translate API.

[0572] 4. The translation results are compared with the ride reservation information.

[0573] example:

[0574] Take a picture of your passport and start the OCR process. The process is complete. Your passport information has been converted to text.

[0575] The OCR extracted text was then translated to "Hello." The translated text was then matched against the reservation system to verify the identity of the person.

[0576] In this way, this invention will streamline the identity verification process for foreign tourists when using self-driving vehicles, enabling accurate verification in real time.

[0577] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0578] Step 1:

[0579] The user takes a picture of their passport with a smart device (smartphone or tablet) and obtains the image data. Specifically, the user launches the camera app and takes a picture of the passport. The input is the image of the passport taken by the user, and the output is the image data.

[0580] Step 2:

[0581] The terminal uploads the acquired passport image to the server. The terminal has a built-in program that sends the captured image to a specified server URL, which sends the image data to the server in real time. The input is the passport image data, and the output is the image data sent to the server.

[0582] Step 3:

[0583] The server inputs the received passport image into an optical character recognition (OCR) engine to extract text information from the image. Specifically, it uses Tesseract OCR to convert the text information in the image into text data. The input is the passport image data, and the output is the extracted text data.

[0584] Step 4:

[0585] The server passes the text data extracted by OCR to the translation engine and translates it into the specified language. Specifically, the text data is translated using the Google Translate API. The input is the text data extracted by OCR, and the output is the translated text data.

[0586] Step 5:

[0587] The server checks the translated text against the reservation system to verify that the user is a valid reservation holder. Specifically, it performs a database query to verify a match against the reservation information. The input is the translated text and the reservation system data, and the output is the identity verification result.

[0588] Step 6:

[0589] The server records all processing steps in a log and saves the audit data. Specifically, it records the details of the processing performed at each step and the results, and saves them in log management software such as ElasticSearch. The input is the result data of each processing step, and the output is the saved log data.

[0590] This processing flow automates the entire process, from taking passport photos to identity verification and log management, ensuring smooth identity verification for foreign tourists when using self-driving vehicles.

[0591] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0592] System Overview

[0593] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones and other devices, translates the contents, and reviews them. It also combines an emotion engine that recognizes the user's emotions. This system converts passport images taken by users into text data using AI-OCR technology, which then translates the data for accurate review. It also recognizes the user's emotions, records the user's emotional state during the review process, and provides feedback as needed.

[0594] System configuration

[0595] 1. Passport Image Capture Module

[0596] The user takes a photo of their passport using their handheld device. The device also uses a camera and microphone to capture the image and to recognize the user's emotions. This data is then uploaded to the server.

[0597] 2. Receiving and OCR module

[0598] The server processes the received image file and emotion data, and uses an AI-OCR engine to extract text data from the passport image.

[0599] 3. Translation Module

[0600] The server passes the extracted text to a translation engine for translation into a specific language, while simultaneously analyzing the user's emotional data and recording the user's emotional state during the review process.

[0601] 4. Review Module

[0602] The server then compares the translated text with the necessary information, such as passport number and name, to verify it against the screening criteria. Furthermore, an emotion engine evaluates the user's emotional state and provides feedback to ensure the fairness of the screening process and the user's sense of security.

[0603] 5. Log Management Module

[0604] The server logs all processing results and emotion data and stores audit data to ensure processing traceability.

[0605] Program processing

[0606] Capture and upload a passport image

[0607] The user takes a passport photo with the device's camera and records their own face and voice to obtain emotion data, which is then uploaded to the server.

[0608] Extracting text data using OCR

[0609] The server processes the received passport image with an AI-OCR engine, extracts text information from the image, and simultaneously analyzes the received emotional data to obtain the user's emotional state. For example, it determines whether the user is relaxed or anxious.

[0610] Translation processing and sentiment analysis

[0611] The server passes the text data extracted by OCR to a translation engine, which translates it into the specified language (e.g., English). In parallel, the emotion engine analyzes the user's emotion data and detects significant emotional changes.

[0612] Review and feedback of input data

[0613] The server then checks the translated text against pre-defined criteria. To ensure fairness in the review, the system also evaluates the user's emotional state and provides appropriate feedback. For example, if the user is feeling anxious, the system can send a reassuring message.

[0614] Logging and Auditing

[0615] The server records detailed logs of all processing steps and the corresponding emotion data. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[0616] Specific examples

[0617] The user takes a photo of their passport on their device and uploads it to the server, while simultaneously capturing a photo of their face to obtain emotional data. The device displays "Uploading image to server," and once the upload is complete, it displays "Upload completed."

[0618] The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and simultaneously performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[0619] The server uses a translation module to translate the extracted text and analyze the sentiment data to obtain insights necessary for review. The log records, "Text translation and sentiment analysis completed."

[0620] The server reviews the translated text and confirms the results while assessing the user's emotional state. It provides feedback to the user as needed. The log states, "Review completed. Recording results and feedback."

[0621] In this way, the present invention can efficiently process passport contents written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[0622] The processing flow will be explained below.

[0623] Step 1:

[0624] The user takes a picture of their passport using their device. The device's camera function is activated and the entire passport is captured clearly. At the same time, the user's face and voice are also recorded, and emotional data is acquired. This image and emotional data are then stored on the device.

[0625] Step 2:

[0626] The device uploads the passport image and emotion data it has taken to the specified server URL. The device then sends the image file (e.g., passport.jpg) and emotion data to the server using an HTTP POST request. During this process, the device displays a message to the user saying, "Sending image and emotion data to server."

[0627] Step 3:

[0628] The server receives the uploaded image and emotion data. The server temporarily stores this data and proceeds to the next processing step. The server log records "Passport image and emotion data received."

[0629] Step 4:

[0630] The server passes the received passport image to the AI-OCR engine, which extracts text information from the image. The OCR engine analyzes the image file and outputs it as text data. At the same time, the emotion engine analyzes the received emotion data. The server log records, "OCR processing and emotion analysis completed."

[0631] Step 5:

[0632] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[0633] Step 6:

[0634] The server obtains the text data translated by the translation engine and passes it to the review module. The review module compares the translated text with pre-set reference data to confirm whether they match. At the same time, it evaluates the emotional data analyzed by the emotion engine to ensure the fairness of the review process. The server log records "Review and emotion evaluation completed."

[0635] Step 7:

[0636] The server provides feedback to the user based on the review results and emotional data. For example, if the user is feeling anxious, it will send a reassuring message. The user can check the results and feedback on their device. The server log will record "Feedback has been sent to the user."

[0637] Step 8:

[0638] The server records all processing results and emotion data in a detailed log and saves it as audit data. This log is used for future review and troubleshooting. The server log will record "All processing has been logged."

[0639] This series of steps allows for efficient processing of passports submitted by users written in foreign languages ​​and highly accurate screening. Furthermore, by using an emotion engine, a fair screening process is realized that takes into account the user's emotional state. This significantly improves the reliability and efficiency of contract procedures.

[0640] Example 2

[0641] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0642] When foreigners apply for a contract for a mobile phone or other device, the details of their passport must be accurately analyzed and reviewed. However, it is difficult to process passport details written in a foreign language quickly and accurately. Furthermore, there is a lack of a system to alleviate the anxiety and stress users may feel during the process. Furthermore, traceable log management is necessary to ensure the fairness and transparency of the process.

[0643] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for acquiring emotional data from the user, means for analyzing the acquired emotional data, means for reviewing the translated text data, means for providing feedback based on the review results and the emotional data, and means for recording the processing steps and the emotional data in a log. This enables a fair review process that takes into account the emotional state of the user while efficiently processing the contents of a passport written in a foreign language, and highly transparent log management.

[0644] The "means for receiving a passport image" is a function for transmitting image data of a passport taken by a user using a terminal to a server, and for the server to receive the image data.

[0645] The "means for extracting characters as text data from a received passport image" is a function that uses optical character recognition (OCR) technology to extract character information from a received passport image as digital text data.

[0646] The "means for translating extracted text data" is a function for converting text data extracted by OCR into a specified language using a multilingual translation engine.

[0647] The "means for acquiring emotional data from the user" is a function for detecting and acquiring the emotional state of the user using the user's facial image and voice data.

[0648] The "means for analyzing acquired emotional data" is a function for analyzing acquired emotional data and grasping the emotions (relaxation, tension, anxiety, etc.) that the user is experiencing.

[0649] The "means for reviewing translated text data" refers to a function for comparing the translated text data with pre-established review criteria to confirm its accuracy and suitability.

[0650] "Means for providing feedback based on the screening results and emotional data" is a function that provides appropriate feedback to the user (such as a message that gives a sense of security or instructions on the next steps) based on the screening results and emotional data.

[0651] The "means for logging processing steps and emotional data" refers to a function that records all processing steps and the corresponding emotional data in detail as a log and saves it for future audits and troubleshooting.

[0652] The present invention is a system used by foreigners when completing procedures such as signing a mobile phone contract, and combines passport image analysis, translation, and user emotion recognition. Details for implementing this system are described below.

[0653] System configuration

[0654] 1. Passport Image Capture Module

[0655] The user takes a photo of their passport using the camera on their device. The system also captures emotional data, such as the user's face and voice, which are then encoded and uploaded to the server.

[0656] 2. Receiving and OCR module

[0657] The server receives the passport image and emotion data sent by the user. It then uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text data from the received passport image. In parallel, the emotion data is also analyzed to understand the user's emotional state.

[0658] 3. Translation Module

[0659] The server passes the text data extracted by the AI-OCR engine to a translation engine (e.g., Google Translate API) and translates it into the specified language (e.g., English). At the same time, it also uses an emotion engine to analyze emotion data and records changes in the user's emotional state.

[0660] 4. Review Module

[0661] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, issue date, expiration date, etc.) to verify accuracy and consistency. Furthermore, it evaluates the emotional data analyzed by the emotion engine and provides feedback to the user to maintain a fair review process.

[0662] 5. Log Management Module

[0663] The server records and stores detailed logs of all processing steps and the corresponding emotion data, ensuring transparency and traceability of the system and allowing for future review and troubleshooting.

[0664] Example

[0665] 1. The user takes a photo of their passport on their device and uploads it to the server, while simultaneously recording their facial image and voice to obtain emotional data. The device displays "Uploading image to server" and notifies them that "Upload completed" when the upload is complete.

[0666] 2. The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[0667] 3. The server uses the translation module to translate the extracted text and analyze the sentiment data to obtain insights needed for review. The log records, "Text translation and sentiment analysis completed."

[0668] 4. The server reviews the translated text, assesses the user's emotional state, and confirms the results. It provides feedback to the user if necessary. The log records, "Review completed. Feedback has been sent to the user."

[0669] 5. The server records all processing steps and emotion data in a detailed log and stores it for future auditing. The log will state, "All processing steps completed. Log data stored."

[0670] Prompt Sentence Examples

[0671] The following prompt sentences can be input to the generative AI model:

[0672] "Please build a system that analyzes an image of my passport, translates and reviews the contents, and simultaneously assesses my emotional state. Please explain the specific steps and technologies used."

[0673] In this way, the embodiments of the invention effectively process the contents of passports written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[0674] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0675] Step 1: Taking a passport photo and acquiring emotion data

[0676] The user takes a passport image using the camera on their device. At the same time, emotional data such as their face and voice are captured. Specifically, the user captures this data by pressing the capture button using a camera and microphone with facial recognition capabilities. The device encodes this data and uploads it to the server. The input is the image captured by the device camera and the recorded voice data, and the output is a data packet containing these uploaded to the server.

[0677] Step 2: Receiving and storing data

[0678] The server receives data packets sent by the user. The server stores the passport image file and emotion data (face image and voice data) in its respective data storage. The input is a data packet containing the image and emotion data from the user terminal, and the output is the passport image file and emotion data stored in the data storage.

[0679] Step 3: Extract text data using OCR

[0680] The server inputs the saved passport image into an AI-OCR engine (for example, Google Cloud Vision API) and extracts text information from the image. Specifically, the passport image data is passed to the engine, and text data such as the name and passport number is extracted from it. The input is the saved passport image file, and the output is the extracted text data.

[0681] Step 4: Analyze the sentiment data

[0682] The server inputs the stored facial image and voice data into an emotion engine to analyze the user's emotional state. Specifically, it uses facial expression recognition and voice analysis technology to evaluate the user's emotions, such as whether they are relaxed or anxious. The input is the stored facial image and voice data, and the output is the analyzed emotional state data.

[0683] Step 5: Translating the text data

[0684] The server passes the text data extracted by OCR to a translation engine (e.g., Google Translate API) to translate it into the specified language. For example, translating Japanese text into English. The input is the extracted text data, and the output is the translated text data.

[0685] Step 6: Review and evaluate the translation data

[0686] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, expiration date, etc.) to verify its accuracy and suitability. At the same time, it evaluates the emotion data to ensure that the review is fair. The input is the translated text data and the analyzed emotion data, and the output is the review result.

[0687] Step 7: Provide feedback to users

[0688] The server provides appropriate feedback to the user based on the evaluation result and emotion data. For example, if the user feels anxious, it sends a message such as "Everything is fine. Don't worry." The input is the evaluation result and emotion data, and the output is the feedback message sent to the user.

[0689] Step 8: Logging and Auditing

[0690] The server records and stores detailed logs of all processing steps and corresponding emotion data for later review and troubleshooting. The inputs are each processing step and its output data, and the output is the stored log data.

[0691] (Application example 2)

[0692] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0693] It is difficult to efficiently and accurately verify the identity of foreign users of self-driving vehicles, and there are also lack of measures to alleviate anxiety caused by language differences and cultural backgrounds. Therefore, it is necessary to provide a sense of security to foreign users in self-driving vehicles by quickly and accurately authenticating them and at the same time taking into account their emotional state.

[0694] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0695] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for examining the translated text data, an emotion engine for recognizing a user's emotion, means for recording the user's emotional state and providing feedback as necessary, and means for processing passport recognition and the user's emotional state within the self-driving vehicle. This makes it possible to quickly and accurately verify the identity of foreign users of self-driving vehicles and provide feedback according to their emotional state.

[0696] "Means for receiving a passport image" refers to a device or method that has the function of taking or scanning an image of the passport presented by the user and transmitting it to the system.

[0697] The "means for extracting characters as text data" refers to a device or method that has the function of recognizing character information from a received passport image and converting it into digital text data.

[0698] The "means for translating extracted text data" refers to a device or method that has the function of translating text data obtained by OCR (Optical Character Recognition) into a different language.

[0699] "Means for reviewing translated text data" means a device or method that has the function of checking and verifying translated text data against pre-established criteria.

[0700] An "emotion engine that recognizes the user's emotions" is a device or software that has the function of analyzing the user's facial expressions, voice, etc. and determining their emotional state.

[0701] A "means for recording a user's emotional state and providing feedback as needed" is a device or method capable of recording a user's emotional state and providing reassuring messages or other feedback based on that data.

[0702] "Means for recognizing passports and processing the emotional state of users within an autonomous vehicle" refers to a device or method that is a system installed in an autonomous vehicle and has the function of recognizing the passport information of foreign users and analyzing the emotional state of the users to respond appropriately.

[0703] MODE FOR CARRYING OUT THE INVENTION

[0704] System configuration

[0705] This invention is a system for efficiently and accurately implementing passport-based authentication procedures for foreign users in automated driving vehicles. The system is composed of the following main components:

[0706] 1. Passport Image Capture Module

[0707] When a user gets into an autonomous vehicle, the device uses a camera installed inside the vehicle to take an image of the user's passport, and also captures video of the user's face to obtain emotional data.

[0708] 2. Data transmission module

[0709] The device transmits the acquired passport image and emotion data to a server via an internet connection.

[0710] 3. OCR and Translation Module

[0711] The server processes the received passport image using an AI-OCR engine to extract text information from the image, and then passes the extracted text data to a translation engine (e.g., Google Translate) to translate it into a specific language.

[0712] 4. Sentiment Analysis Module

[0713] The server analyzes the received emotion data and determines the user's emotional state using software such as the Facial Recognition Library.

[0714] 5. Review and Feedback Module

[0715] The server then authenticates the user based on the translated text data, comparing it with pre-defined criteria, while simultaneously recording the user's emotional state and sending reassuring feedback to the device as needed.

[0716] Program processing

[0717] The processing of each module is carried out as follows.

[0718] Passport image capture: The device takes a passport image using the in-car camera and simultaneously captures a video of the user's face. This data is temporarily stored on the device.

[0719] Data transmission: The device transmits the stored passport image and facial video to a server via the Internet.

[0720] OCR and translation: The server uses OpenCV and Pytesseract to perform OCR on the received passport image and extract text data, which is then translated into the specified language using the Google Translate API.

[0721] Emotion Analysis: The server analyzes the captured facial video using the Facial Recognition Library to determine the user's emotional state. This data is used as key insight into the review process.

[0722] Verification and feedback: The server performs authentication based on the translated text data, comparing it with pre-defined criteria. Depending on the user's emotional state, it sends appropriate feedback messages (e.g., "The process is going smoothly" or "Don't worry, please wait a moment for the process") to the terminal and displays them to the user.

[0723] Specific examples

[0724] As a concrete example, consider the following scenario.

[0725] 1. A user enters an autonomous vehicle and takes a photo of their passport using the device. The device displays "Sending image."

[0726] 2. The device sends the passport image and facial video to the server.

[0727] 3. The server processes the images with OCR, translates the text data, and analyzes the emotions in the facial images.

[0728] 4. The server judges the results of the evaluation and sends feedback to the device according to the user's emotional state.

[0729] 5. The device will display "The process is going smoothly" or "Don't worry, the process will take a moment."

[0730] Example prompt for a generative AI model:

[0731] The user takes a photo of their passport on the tablet and the message "Sending image" appears. The server then processes the image with OCR, translates it, and performs sentiment analysis, displaying feedback based on the user's emotional state. For example, "The process is going smoothly" or "Don't worry, please wait a moment while the process is completed."

[0732] In this way, the present invention makes it possible to quickly and accurately verify the identity of foreign users in self-driving vehicles and provide appropriate feedback according to their emotional state.

[0733] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0734] Program processing steps

[0735] Step 1:

[0736] The device is a camera installed in an autonomous vehicle that captures the user's passport image and facial video. The input is the passport image and the user's facial video, which are temporarily stored on the device. Specifically, the device's camera app is launched, the user is instructed to show their passport, and the image is taken by pressing the shutter button.

[0737] Step 2:

[0738] The device sends the captured passport image and facial video to the server. The input is the passport image and facial video stored on the device, and the output is data sent over the Internet. Specifically, the device's network module is used to send an HTTP POST request to the specified server URL.

[0739] Step 3:

[0740] The server extracts text data from the received passport image using an AI-OCR engine. The input is the passport image, and the output is the extracted text data. Specifically, the image is read using OpenCV, and text information is extracted from the image using Pytesseract.

[0741] Step 4:

[0742] The server passes the extracted text data to a translation engine for translation into a specific language. The input is OCR-processed text data, and the output is translated text data. Specifically, the text data is sent to the Google Translate API and the translated results are received.

[0743] Step 5:

[0744] The server analyzes the received facial video using an emotion analysis module to determine the user's emotional state. The input is the user's facial video, and the output is the analyzed emotional data. Specifically, the server processes the facial video using the Facial Recognition Library and classifies the emotional state.

[0745] Step 6:

[0746] The server compares the translated text data with the authentication criteria to confirm a match. At the same time, it records the user's emotional state and sends feedback as needed. The input is the translated text data and emotional data, and the output is the authentication result and a feedback message based on the emotion. Specifically, it compares the data with a pre-configured authentication criteria database to verify whether the user meets the authentication criteria, and generates a feedback message along with the authentication result.

[0747] Step 7:

[0748] The terminal displays the feedback message received from the server. The input is the feedback message sent from the server, and the output is the message displayed on the terminal display. As a specific operation, the message is displayed using a UI component that displays the message on the terminal display.

[0749] Through these processing steps, the system can quickly and accurately verify the identity of foreign users in autonomous vehicles and provide appropriate feedback according to their emotional state.

[0750] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0751] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0752] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0753] [Third embodiment]

[0754] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0755] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0756] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0757] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0758] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0759] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0760] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0761] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0762] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0763] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0764] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0765] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0766] System Overview

[0767] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones, etc., and translates and examines the contents. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the contents accurately.

[0768] System configuration

[0769] 1. Passport Image Capture Module

[0770] Users take a picture of their passport using their handheld device, which then uploads the image to the server.

[0771] 2. Receiving and OCR module

[0772] The server passes the received image file to the AI-OCR engine to extract text data from the image.

[0773] 3. Translation Module

[0774] The server uses the extracted text in a translation engine to translate it into the specified language.

[0775] 4. Review Module

[0776] The server then uses the translated text to verify necessary information such as passport number and name against the screening criteria.

[0777] 5. Log Management Module

[0778] The server logs all transaction results and stores audit data to ensure transaction traceability.

[0779] Program processing

[0780] Capture and upload a passport image

[0781] The user takes a photo of their passport using the device's camera and uploads it to a specified server URL. The device is equipped with a program that sends the captured image file to the server, thereby sending the image data in real time.

[0782] Extracting text data using OCR

[0783] The server processes the passport image it receives with an AI-OCR engine. The OCR engine automatically detects text information in the image and converts it into text data. For example, information such as passport number, name, and place of birth is converted into text.

[0784] Translation Processing

[0785] The server then passes the extracted text data to a translation engine for translation into a specific language. This uses common translation services such as Google Translate API to ensure fast and accurate translation.

[0786] Input data review

[0787] The server receives the translated text data and checks it against pre-defined criteria, such as whether the passport number or the applicant's name matches the data in the system. Based on the results of this check, it decides whether the application is approved or not.

[0788] Logging and Auditing

[0789] The server logs all processing steps in detail. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[0790] Specific examples

[0791] The user takes a photo of their passport on their device and uploads it to the server. At that time, the message displayed on the device is "Uploading image to server," and after the transfer is complete, the message "Upload completed" is displayed.

[0792] The server receives the image and extracts the text information from the passport through the OCR module. The log records "OCR processing completed. Extracted text will be displayed."

[0793] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[0794] The server reviews the translated text in the review module and confirms the result. The log will say "Review completed. Recording the result."

[0795] In this way, the present invention makes it possible to efficiently and accurately inspect passports written in foreign languages, thereby facilitating the smooth processing of contracts for mobile phones and other devices.

[0796] The processing flow will be explained below.

[0797] Step 1:

[0798] The user takes a picture of the passport using their device, activates the device's camera function, and takes a picture so that the entire passport is clearly visible. After checking the image, the user saves it on the device.

[0799] Step 2:

[0800] The device uploads the passport image it has taken to the specified server URL. The device sends the image file (e.g., passport.jpg) to the server using an HTTP POST request. During this process, the device displays the message "Sending image to server" to the user.

[0801] Step 3:

[0802] The server receives the uploaded image, temporarily stores the image data, and then proceeds to the next processing step.

[0803] Step 4:

[0804] The server passes the received passport image to the AI-OCR engine and extracts text information from the image. To do this, the image file is first read into the OCR engine and output as text data. The server log records "OCR processing completed."

[0805] Step 5:

[0806] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[0807] Step 6:

[0808] The server passes the translated text data to the review module for review. The server compares the translated text with pre-defined reference data to ensure that they match. For example, it verifies that the passport number and name match the reference data.

[0809] Step 7:

[0810] The server records the results of the review in a log. If necessary, it notifies the user of the results. The server's log records "The review has been completed. The results will be recorded." At this stage, the entire process is complete.

[0811] The above steps enable efficient processing of passports written in foreign languages ​​submitted by users and highly accurate screening, significantly improving the reliability and efficiency of contract procedures.

[0812] Example 1

[0813] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0814] Conventional passport inspection systems lack sufficient automation for character recognition and translation of passports written in foreign languages, resulting in time-consuming and labor-intensive processes. There was also room for improvement in the accuracy and efficiency of inspections. This created a growing need for a system that could quickly and accurately extract passport text data, automatically translate it, and inspect it. Furthermore, there was a need for detailed log management to ensure transparency and traceability of processing.

[0815] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0816] In this invention, the server includes a means for taking a passport image using a terminal and uploading it to the server, a means for processing the received passport image with an optical character recognition engine to extract characters as text data, a means for translating the extracted text data into a specified language using a translation engine, a means for comparing the translated text data with preset standards and reviewing it, and a means for recording all processing steps in detail in a log and saving it for audit purposes. This makes it possible to efficiently and accurately recognize, translate, and review passports written in foreign languages, thereby smoothly progressing contract procedures. Furthermore, log management ensures system transparency and traceability, improving reliability.

[0817] A "terminal" is an electronic device used by a user, such as a mobile phone, smartphone, or tablet, that has a camera function.

[0818] A "server" is a computer system that receives and processes data from terminals via a network, and analyzes and reviews it using various engines.

[0819] "Passport image" is a photograph of a travel document taken by a user with the camera on the terminal, and is image data used for various inspections.

[0820] An "optical character recognition engine (OCR engine)" is a general term for software that detects character information from image data and converts it into text data.

[0821] "Text data" is a data format that includes character information extracted by an OCR engine, and is the content of a document recognized as a string of characters.

[0822] A "translation engine" is software or a service for translating strings from one language to another.

[0823] "Criteria" are pre-defined evaluation criteria or conditions used when reviewing text data.

[0824] "Review" is the process of comparing the extracted and translated text data with standards to confirm matches.

[0825] A "log" is data that describes the work history and results recorded at each processing step of the system.

[0826] "Stored for audit" means storing processing history and results in a secure location for future verification and troubleshooting.

[0827] MODE FOR CARRYING OUT THE INVENTION

[0828] This invention relates to a system that analyzes passport images presented by foreigners, translates their contents, and examines them. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the data, enabling smooth contract procedures for mobile phones and other devices.

[0829] Hardware and Software Configuration

[0830] The hardware used includes a terminal (such as a smartphone or tablet) and a server. The terminal has a camera function that the user uses to take a passport image.

[0831] The software consists of the following:

[0832] 1. Passport Image Capture Module:

[0833] The user takes a picture of the passport using the device's camera and sends it to the server using a dedicated upload application.

[0834] 2. Receiving and OCR module:

[0835] The server saves the received image files in a specific folder and extracts the text information using an AI-OCR engine, such as the Google Cloud Vision API.

[0836] 3. Translation Module:

[0837] The server sends the text data generated by OCR to a translation engine (such as Google Translate API) and translates it into the specified language.

[0838] 4. Review Module:

[0839] The server reviews the translated text data against pre-set criteria and verifies necessary information such as passport number and name.

[0840] 5. Log Management Module:

[0841] The server will log all transaction results in detail and store audit data to ensure transaction traceability.

[0842] Specific examples

[0843] The user takes a photo of their passport on their device and sends it to the server using a dedicated upload application. The message displayed on the device is "Uploading image to server," and after sending is complete, the message "Upload completed" is displayed.

[0844] The server passes the received image file to the AI-OCR engine for processing. For example, it logs a message saying, "OCR processing completed. Extracted text displayed."

[0845] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[0846] The server evaluates the translated text in the review module and confirms the result. The log will say "Review completed. Recording result."

[0847] Prompt Sentence Examples

[0848] Here are some example prompts for the generative AI model:

[0849] 1. Prompt:

[0850] Upload passport images and create a program that uses AI-OCR and a translation engine to examine the contents of foreign passports.

[0851] 2. Examples of prompts:

[0852] Build a system that takes a photo of a foreigner's passport with a smartphone camera and uploads it to a server, which then extracts text using AI-OCR and translates it using the Google Translate API, and then automatically reviews the passport contents based on that.

[0853] In this way, by clearly specifying the specific processing steps and the hardware and software to be used, it is possible to provide a system that can efficiently process passport contents written in a foreign language and carry out contract procedures smoothly.

[0854] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0855] Program processing flow

[0856] Step 1: Capture and upload a passport image

[0857] Input: Passport image taken by the user using the device camera

[0858] Output: Image file uploaded to the server

[0859] 1. The user launches the camera application on the device.

[0860] 2. The user uses the camera application to take an image containing the entire passport.

[0861] 3. The device displays an interface for uploading the captured images to the server using a dedicated application.

[0862] 4. The user taps the "Upload image" button, and the device sends the image file to the specified server URL. For example, a message appears saying "Uploading image to server."

[0863] 5. Once the image upload is complete, the device will display "Upload complete."

[0864] Step 2: Receiving images and extracting text data using OCR

[0865] Input: Passport image file uploaded to the server

[0866] Output: Text data extracted by OCR

[0867] 1. The server saves the uploaded image files in a specific folder.

[0868] 2. The server passes the saved image file to the AI-OCR engine, which uses the Google Cloud Vision API or similar.

[0869] 3. The AI-OCR engine analyzes the text information in the image and extracts text data such as passport number, name, and place of birth.

[0870] 4. The server temporarily stores the extracted text data in an internal database.

[0871] 5. The processing log will record "OCR processing completed. Extracted text: [Extracted text]".

[0872] Step 3: Translating the text data

[0873] Input: Text data extracted by OCR

[0874] Output: Text data translated by the translation engine

[0875] 1. The server reads the temporarily stored text data and connects to a translation engine (such as Google Translate API).

[0876] 2. The server passes the text data to the translation engine and requests translation into the specified language.

[0877] 3. The translation engine translates the text data into the specified language and returns the translated text data to the server.

[0878] 4. The server receives the translation results and stores them in memory or a database.

[0879] 5. Record the following in the processing log: "Text translation completed. Translation result: [translated text]."

[0880] Step 4: Translation review

[0881] Input: Translated text data

[0882] Output: Review results

[0883] 1. The server reads the pre-defined review criteria from the database.

[0884] 2. The server compares the translation data with the review criteria and confirms a match.

[0885] 3. For example, checking that translated passport numbers are in a valid format and names follow a specific format.

[0886] 4. The server generates the review results and records them in the database.

[0887] 5. Record "Review completed. Result: [Review result]" in the processing log.

[0888] Step 5: Log Management and Auditing

[0889] Input: Execution results and status data for each processing step

[0890] Output: Detailed log files and audit data

[0891] 1. The server records all processing results and times in a log file for each step of image reception, OCR processing, translation processing, and review.

[0892] 2. The server stores the status (success / failure) and detailed error message for each operation.

[0893] 3. The server will regularly back up audit log data and store it in secure storage.

[0894] 4. The server uses these logs for future audits and troubleshooting.

[0895] 5. Record "Log management and audit data storage completed" in the processing log.

[0896] This enables the system to efficiently and accurately analyze passports written in foreign languages, facilitating smooth contract procedures.

[0897] (Application example 1)

[0898] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0899] Conventional identity verification systems using passport information have difficulty handling passports written in multiple languages, making accurate identity verification difficult. Furthermore, because real-time processing was not possible, the verification process took time, resulting in poor user convenience. Furthermore, the lack of traceability and transparency in the process made auditing and troubleshooting difficult.

[0900] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0901] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for reviewing the translated text data, means for taking a passport image with a smart device and processing it in real time, means for verifying the identity of the person by comparing the translated text data with the reservation system, and means for recording all processing steps in a log. This enables accurate real-time identity verification in multiple languages, improving user convenience. It also ensures traceability and transparency of the process, facilitating audits and troubleshooting.

[0902] The "means for receiving a passport image" is a combination of hardware and software that allows a user to take an image of their passport and send the image data to a server.

[0903] The "means for extracting characters from a received passport image as text data" is a system that includes a process of analyzing a received passport image, extracting character information using optical character recognition technology, and converting it into text data.

[0904] "Means for translating extracted text data" refers to software and algorithms for translating the text data extracted by optical character recognition technology into another specified language, such as by using an online translation service or a translation API.

[0905] The "means for reviewing translated text data" refers to a system that structures translated text data and reviews it by comparing it with pre-established standards or databases.

[0906] "Means for taking passport images using a smart device and processing them in real time" refers to hardware and software that allows a passport image to be taken using a mobile device such as a smartphone or tablet, and then immediately sends the image to a server to begin analysis.

[0907] "Means for verifying identity by comparing translated text data with the reservation system" refers to a system that compares translated passport information with the database of the existing reservation system to confirm a match and verify that the user is a legitimate person making a reservation.

[0908] "Means for logging all processing steps" refers to a system that records in detail all processing steps, including receipt, OCR processing, translation, and review, and saves the log data. This ensures traceability and transparency of the process.

[0909] MODE FOR CARRYING OUT THE INVENTION

[0910] The following describes in detail the mode for carrying out this invention. This system is designed to verify the identity of foreign tourists using passport information when they use an automated driving vehicle. The system is composed of the following main components:

[0911] Key Elements

[0912] 1. Passport image capture function

[0913] The user takes a photo of the passport using a smart device (smartphone, tablet, etc.), and the image is uploaded to the server as is.

[0914] 2. Real-time OCR processing

[0915] The server processes the received passport image using an optical character recognition (OCR) engine (e.g., Tesseract OCR) and converts the character information in the image into text data.

[0916] 3. Real-time translation function

[0917] The server translates the text data extracted by OCR into the specified language using an automatic translation engine (e.g., Google Translate API).

[0918] 4. Identity Verification

[0919] The server compares the translated text data with the data in the reservation system to verify that the user is a legitimate user.

[0920] 5. Data log management

[0921] The server logs all processing steps in detail and stores audit data to ensure traceability and transparency of the process.

[0922] Hardware and Software Configuration

[0923] The specific hardware and software used are shown below.

[0924] Smart Devices

[0925] Users take a passport photo using a smart device (smartphone or tablet) and upload the image to the server.

[0926] server

[0927] The following software is installed on the server:

[0928] Optical Character Recognition Engine: Tesseract OCR

[0929] Machine translation engine: Google Translate API

[0930] Database system: SQLite or other database system

[0931] Log management software: ElasticSearch, etc.

[0932] Example of operation

[0933] As an example, consider a scenario where a foreign tourist boards an autonomous vehicle. The tourist uses a smart device to take a photo of their passport. The image data is sent to a server in real time and converted into text data using OCR technology. The text data is translated using the Google Translate API and matched with data from the reservation system. Finally, all processing steps are logged to enable future audits and troubleshooting.

[0934] Example prompt sentence:

[0935] Passport authentication process in autonomous vehicle boarding verification system:

[0936] 1. Travelers capture a passport image with their smartphone.

[0937] 2. Extract text data from images using an OCR engine.

[0938] 3. Translate the extracted text into Japanese using the Google Translate API.

[0939] 4. The translation results are compared with the ride reservation information.

[0940] example:

[0941] Take a picture of your passport and start the OCR process. The process is complete. Your passport information has been converted to text.

[0942] The OCR extracted text was then translated to "Hello." The translated text was then matched against the reservation system to verify the identity of the person.

[0943] In this way, this invention will streamline the identity verification process for foreign tourists when using self-driving vehicles, enabling accurate verification in real time.

[0944] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0945] Step 1:

[0946] The user takes a picture of their passport with a smart device (smartphone or tablet) and obtains the image data. Specifically, the user launches the camera app and takes a picture of the passport. The input is the image of the passport taken by the user, and the output is the image data.

[0947] Step 2:

[0948] The terminal uploads the acquired passport image to the server. The terminal has a built-in program that sends the captured image to a specified server URL, which sends the image data to the server in real time. The input is the passport image data, and the output is the image data sent to the server.

[0949] Step 3:

[0950] The server inputs the received passport image into an optical character recognition (OCR) engine to extract text information from the image. Specifically, it uses Tesseract OCR to convert the text information in the image into text data. The input is the passport image data, and the output is the extracted text data.

[0951] Step 4:

[0952] The server passes the text data extracted by OCR to the translation engine and translates it into the specified language. Specifically, the text data is translated using the Google Translate API. The input is the text data extracted by OCR, and the output is the translated text data.

[0953] Step 5:

[0954] The server checks the translated text against the reservation system to verify that the user is a valid reservation holder. Specifically, it performs a database query to verify a match against the reservation information. The input is the translated text and the reservation system data, and the output is the identity verification result.

[0955] Step 6:

[0956] The server records all processing steps in a log and saves the audit data. Specifically, it records the details of the processing performed at each step and the results, and saves them in log management software such as ElasticSearch. The input is the result data of each processing step, and the output is the saved log data.

[0957] This processing flow automates the entire process, from taking passport photos to identity verification and log management, ensuring smooth identity verification for foreign tourists when using self-driving vehicles.

[0958] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0959] System Overview

[0960] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones and other devices, translates the contents, and reviews them. It also combines an emotion engine that recognizes the user's emotions. This system converts passport images taken by users into text data using AI-OCR technology, which then translates the data for accurate review. It also recognizes the user's emotions, records the user's emotional state during the review process, and provides feedback as needed.

[0961] System configuration

[0962] 1. Passport Image Capture Module

[0963] The user takes a photo of their passport using their handheld device. The device also uses a camera and microphone to capture the image and to recognize the user's emotions. This data is then uploaded to the server.

[0964] 2. Receiving and OCR module

[0965] The server processes the received image file and emotion data, and uses an AI-OCR engine to extract text data from the passport image.

[0966] 3. Translation Module

[0967] The server passes the extracted text to a translation engine for translation into a specific language, while simultaneously analyzing the user's emotional data and recording the user's emotional state during the review process.

[0968] 4. Review Module

[0969] The server then compares the translated text with the necessary information, such as passport number and name, to verify it against the screening criteria. Furthermore, an emotion engine evaluates the user's emotional state and provides feedback to ensure the fairness of the screening process and the user's sense of security.

[0970] 5. Log Management Module

[0971] The server logs all processing results and emotion data and stores audit data to ensure processing traceability.

[0972] Program processing

[0973] Capture and upload a passport image

[0974] The user takes a passport photo with the device's camera and records their own face and voice to obtain emotion data, which is then uploaded to the server.

[0975] Extracting text data using OCR

[0976] The server processes the received passport image with an AI-OCR engine, extracts text information from the image, and simultaneously analyzes the received emotional data to obtain the user's emotional state. For example, it determines whether the user is relaxed or anxious.

[0977] Translation processing and sentiment analysis

[0978] The server passes the text data extracted by OCR to a translation engine, which translates it into the specified language (e.g., English). In parallel, the emotion engine analyzes the user's emotion data and detects significant emotional changes.

[0979] Review and feedback of input data

[0980] The server then checks the translated text against pre-defined criteria. To ensure fairness in the review, the system also evaluates the user's emotional state and provides appropriate feedback. For example, if the user is feeling anxious, the system can send a reassuring message.

[0981] Logging and Auditing

[0982] The server records detailed logs of all processing steps and the corresponding emotion data. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[0983] Specific examples

[0984] The user takes a photo of their passport on their device and uploads it to the server, while simultaneously capturing a photo of their face to obtain emotional data. The device displays "Uploading image to server," and once the upload is complete, it displays "Upload completed."

[0985] The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and simultaneously performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[0986] The server uses a translation module to translate the extracted text and analyze the sentiment data to obtain insights necessary for review. The log records, "Text translation and sentiment analysis completed."

[0987] The server reviews the translated text and confirms the results while assessing the user's emotional state. It provides feedback to the user as needed. The log states, "Review completed. Recording results and feedback."

[0988] In this way, the present invention can efficiently process passport contents written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[0989] The processing flow will be explained below.

[0990] Step 1:

[0991] The user takes a picture of their passport using their device. The device's camera function is activated and the entire passport is captured clearly. At the same time, the user's face and voice are also recorded, and emotional data is acquired. This image and emotional data are then stored on the device.

[0992] Step 2:

[0993] The device uploads the passport image and emotion data it has taken to the specified server URL. The device then sends the image file (e.g., passport.jpg) and emotion data to the server using an HTTP POST request. During this process, the device displays a message to the user saying, "Sending image and emotion data to server."

[0994] Step 3:

[0995] The server receives the uploaded image and emotion data. The server temporarily stores this data and proceeds to the next processing step. The server log records "Passport image and emotion data received."

[0996] Step 4:

[0997] The server passes the received passport image to the AI-OCR engine, which extracts text information from the image. The OCR engine analyzes the image file and outputs it as text data. At the same time, the emotion engine analyzes the received emotion data. The server log records, "OCR processing and emotion analysis completed."

[0998] Step 5:

[0999] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[1000] Step 6:

[1001] The server obtains the text data translated by the translation engine and passes it to the review module. The review module compares the translated text with pre-set reference data to confirm whether they match. At the same time, it evaluates the emotional data analyzed by the emotion engine to ensure the fairness of the review process. The server log records "Review and emotion evaluation completed."

[1002] Step 7:

[1003] The server provides feedback to the user based on the review results and emotional data. For example, if the user is feeling anxious, it will send a reassuring message. The user can check the results and feedback on their device. The server log will record "Feedback has been sent to the user."

[1004] Step 8:

[1005] The server records all processing results and emotion data in a detailed log and saves it as audit data. This log is used for future review and troubleshooting. The server log will record "All processing has been logged."

[1006] This series of steps allows for efficient processing of passports submitted by users written in foreign languages ​​and highly accurate screening. Furthermore, by using an emotion engine, a fair screening process is realized that takes into account the user's emotional state. This significantly improves the reliability and efficiency of contract procedures.

[1007] Example 2

[1008] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1009] When foreigners apply for a contract for a mobile phone or other device, the details of their passport must be accurately analyzed and reviewed. However, it is difficult to process passport details written in a foreign language quickly and accurately. Furthermore, there is a lack of a system to alleviate the anxiety and stress users may feel during the process. Furthermore, traceable log management is necessary to ensure the fairness and transparency of the process.

[1010] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for acquiring emotional data from the user, means for analyzing the acquired emotional data, means for reviewing the translated text data, means for providing feedback based on the review results and the emotional data, and means for recording the processing steps and the emotional data in a log. This enables a fair review process that takes into account the emotional state of the user while efficiently processing the contents of a passport written in a foreign language, and highly transparent log management.

[1011] The "means for receiving a passport image" is a function for transmitting image data of a passport taken by a user using a terminal to a server, and for the server to receive the image data.

[1012] The "means for extracting characters as text data from a received passport image" is a function that uses optical character recognition (OCR) technology to extract character information from a received passport image as digital text data.

[1013] The "means for translating extracted text data" is a function for converting text data extracted by OCR into a specified language using a multilingual translation engine.

[1014] The "means for acquiring emotional data from the user" is a function for detecting and acquiring the emotional state of the user using the user's facial image and voice data.

[1015] The "means for analyzing acquired emotional data" is a function for analyzing acquired emotional data and grasping the emotions (relaxation, tension, anxiety, etc.) that the user is experiencing.

[1016] The "means for reviewing translated text data" refers to a function for comparing the translated text data with pre-established review criteria to confirm its accuracy and suitability.

[1017] "Means for providing feedback based on the screening results and emotional data" is a function that provides appropriate feedback to the user (such as a message that gives a sense of security or instructions on the next steps) based on the screening results and emotional data.

[1018] The "means for logging processing steps and emotional data" refers to a function that records all processing steps and the corresponding emotional data in detail as a log and saves it for future audits and troubleshooting.

[1019] The present invention is a system used by foreigners when completing procedures such as signing a mobile phone contract, and combines passport image analysis, translation, and user emotion recognition. Details for implementing this system are described below.

[1020] System configuration

[1021] 1. Passport Image Capture Module

[1022] The user takes a photo of their passport using the camera on their device. The system also captures emotional data, such as the user's face and voice, which are then encoded and uploaded to the server.

[1023] 2. Receiving and OCR module

[1024] The server receives the passport image and emotion data sent by the user. It then uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text data from the received passport image. In parallel, the emotion data is also analyzed to understand the user's emotional state.

[1025] 3. Translation Module

[1026] The server passes the text data extracted by the AI-OCR engine to a translation engine (e.g., Google Translate API) and translates it into the specified language (e.g., English). At the same time, it also uses an emotion engine to analyze emotion data and records changes in the user's emotional state.

[1027] 4. Review Module

[1028] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, issue date, expiration date, etc.) to verify accuracy and consistency. Furthermore, it evaluates the emotional data analyzed by the emotion engine and provides feedback to the user to maintain a fair review process.

[1029] 5. Log Management Module

[1030] The server records and stores detailed logs of all processing steps and the corresponding emotion data, ensuring transparency and traceability of the system and allowing for future review and troubleshooting.

[1031] Example

[1032] 1. The user takes a photo of their passport on their device and uploads it to the server, while simultaneously recording their facial image and voice to obtain emotional data. The device displays "Uploading image to server" and notifies them that "Upload completed" when the upload is complete.

[1033] 2. The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[1034] 3. The server uses the translation module to translate the extracted text and analyze the sentiment data to obtain insights needed for review. The log records, "Text translation and sentiment analysis completed."

[1035] 4. The server reviews the translated text, assesses the user's emotional state, and confirms the results. It provides feedback to the user if necessary. The log records, "Review completed. Feedback has been sent to the user."

[1036] 5. The server records all processing steps and emotion data in a detailed log and stores it for future auditing. The log will state, "All processing steps completed. Log data stored."

[1037] Prompt Sentence Examples

[1038] The following prompt sentences can be input to the generative AI model:

[1039] "Please build a system that analyzes an image of my passport, translates and reviews the contents, and simultaneously assesses my emotional state. Please explain the specific steps and technologies used."

[1040] In this way, the embodiments of the invention effectively process the contents of passports written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[1041] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1042] Step 1: Taking a passport photo and acquiring emotion data

[1043] The user takes a passport image using the camera on their device. At the same time, emotional data such as their face and voice are captured. Specifically, the user captures this data by pressing the capture button using a camera and microphone with facial recognition capabilities. The device encodes this data and uploads it to the server. The input is the image captured by the device camera and the recorded voice data, and the output is a data packet containing these uploaded to the server.

[1044] Step 2: Receiving and storing data

[1045] The server receives data packets sent by the user. The server stores the passport image file and emotion data (face image and voice data) in its respective data storage. The input is a data packet containing the image and emotion data from the user terminal, and the output is the passport image file and emotion data stored in the data storage.

[1046] Step 3: Extract text data using OCR

[1047] The server inputs the saved passport image into an AI-OCR engine (for example, Google Cloud Vision API) and extracts text information from the image. Specifically, the passport image data is passed to the engine, and text data such as the name and passport number is extracted from it. The input is the saved passport image file, and the output is the extracted text data.

[1048] Step 4: Analyze the sentiment data

[1049] The server inputs the stored facial image and voice data into an emotion engine to analyze the user's emotional state. Specifically, it uses facial expression recognition and voice analysis technology to evaluate the user's emotions, such as whether they are relaxed or anxious. The input is the stored facial image and voice data, and the output is the analyzed emotional state data.

[1050] Step 5: Translating the text data

[1051] The server passes the text data extracted by OCR to a translation engine (e.g., Google Translate API) to translate it into the specified language. For example, translating Japanese text into English. The input is the extracted text data, and the output is the translated text data.

[1052] Step 6: Review and evaluate the translation data

[1053] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, expiration date, etc.) to verify its accuracy and suitability. At the same time, it evaluates the emotion data to ensure that the review is fair. The input is the translated text data and the analyzed emotion data, and the output is the review result.

[1054] Step 7: Provide feedback to users

[1055] The server provides appropriate feedback to the user based on the evaluation result and emotion data. For example, if the user feels anxious, it sends a message such as "Everything is fine. Don't worry." The input is the evaluation result and emotion data, and the output is the feedback message sent to the user.

[1056] Step 8: Logging and Auditing

[1057] The server records and stores detailed logs of all processing steps and corresponding emotion data for later review and troubleshooting. The inputs are each processing step and its output data, and the output is the stored log data.

[1058] (Application example 2)

[1059] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1060] It is difficult to efficiently and accurately verify the identity of foreign users of self-driving vehicles, and there are also lack of measures to alleviate anxiety caused by language differences and cultural backgrounds. Therefore, it is necessary to provide a sense of security to foreign users in self-driving vehicles by quickly and accurately authenticating them and at the same time taking into account their emotional state.

[1061] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1062] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for examining the translated text data, an emotion engine for recognizing a user's emotion, means for recording the user's emotional state and providing feedback as necessary, and means for processing passport recognition and the user's emotional state within the self-driving vehicle. This makes it possible to quickly and accurately verify the identity of foreign users of self-driving vehicles and provide feedback according to their emotional state.

[1063] "Means for receiving a passport image" refers to a device or method that has the function of taking or scanning an image of the passport presented by the user and transmitting it to the system.

[1064] The "means for extracting characters as text data" refers to a device or method that has the function of recognizing character information from a received passport image and converting it into digital text data.

[1065] The "means for translating extracted text data" refers to a device or method that has the function of translating text data obtained by OCR (Optical Character Recognition) into a different language.

[1066] "Means for reviewing translated text data" means a device or method that has the function of checking and verifying translated text data against pre-established criteria.

[1067] An "emotion engine that recognizes the user's emotions" is a device or software that has the function of analyzing the user's facial expressions, voice, etc. and determining their emotional state.

[1068] A "means for recording a user's emotional state and providing feedback as needed" is a device or method capable of recording a user's emotional state and providing reassuring messages or other feedback based on that data.

[1069] "Means for recognizing passports and processing the emotional state of users within an autonomous vehicle" refers to a device or method that is a system installed in an autonomous vehicle and has the function of recognizing the passport information of foreign users and analyzing the emotional state of the users to respond appropriately.

[1070] MODE FOR CARRYING OUT THE INVENTION

[1071] System configuration

[1072] This invention is a system for efficiently and accurately implementing passport-based authentication procedures for foreign users in automated driving vehicles. The system is composed of the following main components:

[1073] 1. Passport Image Capture Module

[1074] When a user gets into an autonomous vehicle, the device uses a camera installed inside the vehicle to take an image of the user's passport, and also captures video of the user's face to obtain emotional data.

[1075] 2. Data transmission module

[1076] The device transmits the acquired passport image and emotion data to a server via an internet connection.

[1077] 3. OCR and Translation Module

[1078] The server processes the received passport image using an AI-OCR engine to extract text information from the image, and then passes the extracted text data to a translation engine (e.g., Google Translate) to translate it into a specific language.

[1079] 4. Sentiment Analysis Module

[1080] The server analyzes the received emotion data and determines the user's emotional state using software such as the Facial Recognition Library.

[1081] 5. Review and Feedback Module

[1082] The server then authenticates the user based on the translated text data, comparing it with pre-defined criteria, while simultaneously recording the user's emotional state and sending reassuring feedback to the device as needed.

[1083] Program processing

[1084] The processing of each module is carried out as follows.

[1085] Passport image capture: The device takes a passport image using the in-car camera and simultaneously captures a video of the user's face. This data is temporarily stored on the device.

[1086] Data transmission: The device transmits the stored passport image and facial video to a server via the Internet.

[1087] OCR and translation: The server uses OpenCV and Pytesseract to perform OCR on the received passport image and extract text data, which is then translated into the specified language using the Google Translate API.

[1088] Emotion Analysis: The server analyzes the captured facial video using the Facial Recognition Library to determine the user's emotional state. This data is used as key insight into the review process.

[1089] Verification and feedback: The server performs authentication based on the translated text data, comparing it with pre-defined criteria. Depending on the user's emotional state, it sends appropriate feedback messages (e.g., "The process is going smoothly" or "Don't worry, please wait a moment for the process") to the terminal and displays them to the user.

[1090] Specific examples

[1091] As a concrete example, consider the following scenario.

[1092] 1. A user enters an autonomous vehicle and takes a photo of their passport using the device. The device displays "Sending image."

[1093] 2. The device sends the passport image and facial video to the server.

[1094] 3. The server processes the images with OCR, translates the text data, and analyzes the emotions in the facial images.

[1095] 4. The server judges the results of the evaluation and sends feedback to the device according to the user's emotional state.

[1096] 5. The device will display "The process is going smoothly" or "Don't worry, the process will take a moment."

[1097] Example prompt for a generative AI model:

[1098] The user takes a photo of their passport on the tablet and the message "Sending image" appears. The server then processes the image with OCR, translates it, and performs sentiment analysis, displaying feedback based on the user's emotional state. For example, "The process is going smoothly" or "Don't worry, please wait a moment while the process is completed."

[1099] In this way, the present invention makes it possible to quickly and accurately verify the identity of foreign users in self-driving vehicles and provide appropriate feedback according to their emotional state.

[1100] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1101] Program processing steps

[1102] Step 1:

[1103] The device is a camera installed in an autonomous vehicle that captures the user's passport image and facial video. The input is the passport image and the user's facial video, which are temporarily stored on the device. Specifically, the device's camera app is launched, the user is instructed to show their passport, and the image is taken by pressing the shutter button.

[1104] Step 2:

[1105] The device sends the captured passport image and facial video to the server. The input is the passport image and facial video stored on the device, and the output is data sent over the Internet. Specifically, the device's network module is used to send an HTTP POST request to the specified server URL.

[1106] Step 3:

[1107] The server extracts text data from the received passport image using an AI-OCR engine. The input is the passport image, and the output is the extracted text data. Specifically, the image is read using OpenCV, and text information is extracted from the image using Pytesseract.

[1108] Step 4:

[1109] The server passes the extracted text data to a translation engine for translation into a specific language. The input is OCR-processed text data, and the output is translated text data. Specifically, the text data is sent to the Google Translate API and the translated results are received.

[1110] Step 5:

[1111] The server analyzes the received facial video using an emotion analysis module to determine the user's emotional state. The input is the user's facial video, and the output is the analyzed emotional data. Specifically, the server processes the facial video using the Facial Recognition Library and classifies the emotional state.

[1112] Step 6:

[1113] The server compares the translated text data with the authentication criteria to confirm a match. At the same time, it records the user's emotional state and sends feedback as needed. The input is the translated text data and emotional data, and the output is the authentication result and a feedback message based on the emotion. Specifically, it compares the data with a pre-configured authentication criteria database to verify whether the user meets the authentication criteria, and generates a feedback message along with the authentication result.

[1114] Step 7:

[1115] The terminal displays the feedback message received from the server. The input is the feedback message sent from the server, and the output is the message displayed on the terminal display. As a specific operation, the message is displayed using a UI component that displays the message on the terminal display.

[1116] Through these processing steps, the system can quickly and accurately verify the identity of foreign users in autonomous vehicles and provide appropriate feedback according to their emotional state.

[1117] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1118] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1119] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1120] [Fourth embodiment]

[1121] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1122] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1123] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1124] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1125] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1126] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1127] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1128] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1129] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1130] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1131] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1132] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1133] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1134] System Overview

[1135] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones, etc., and translates and examines the contents. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the contents accurately.

[1136] System configuration

[1137] 1. Passport Image Capture Module

[1138] Users take a picture of their passport using their handheld device, which then uploads the image to the server.

[1139] 2. Receiving and OCR module

[1140] The server passes the received image file to the AI-OCR engine to extract text data from the image.

[1141] 3. Translation Module

[1142] The server uses the extracted text in a translation engine to translate it into the specified language.

[1143] 4. Review Module

[1144] The server then uses the translated text to verify necessary information such as passport number and name against the screening criteria.

[1145] 5. Log Management Module

[1146] The server logs all transaction results and stores audit data to ensure transaction traceability.

[1147] Program processing

[1148] Capture and upload a passport image

[1149] The user takes a photo of their passport using the device's camera and uploads it to a specified server URL. The device is equipped with a program that sends the captured image file to the server, thereby sending the image data in real time.

[1150] Extracting text data using OCR

[1151] The server processes the passport image it receives with an AI-OCR engine. The OCR engine automatically detects text information in the image and converts it into text data. For example, information such as passport number, name, and place of birth is converted into text.

[1152] Translation Processing

[1153] The server then passes the extracted text data to a translation engine for translation into a specific language. This uses common translation services such as Google Translate API to ensure fast and accurate translation.

[1154] Input data review

[1155] The server receives the translated text data and checks it against pre-defined criteria, such as whether the passport number or the applicant's name matches the data in the system. Based on the results of this check, it decides whether the application is approved or not.

[1156] Logging and Auditing

[1157] The server logs all processing steps in detail. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[1158] Specific examples

[1159] The user takes a photo of their passport on their device and uploads it to the server. At that time, the message displayed on the device is "Uploading image to server," and after the transfer is complete, the message "Upload completed" is displayed.

[1160] The server receives the image and extracts the text information from the passport through the OCR module. The log records "OCR processing completed. Extracted text will be displayed."

[1161] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[1162] The server reviews the translated text in the review module and confirms the result. The log will say "Review completed. Recording the result."

[1163] In this way, the present invention makes it possible to efficiently and accurately inspect passports written in foreign languages, thereby facilitating the smooth processing of contracts for mobile phones and other devices.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] The user takes a picture of the passport using their device, activates the device's camera function, and takes a picture so that the entire passport is clearly visible. After checking the image, the user saves it on the device.

[1167] Step 2:

[1168] The device uploads the passport image it has taken to the specified server URL. The device sends the image file (e.g., passport.jpg) to the server using an HTTP POST request. During this process, the device displays the message "Sending image to server" to the user.

[1169] Step 3:

[1170] The server receives the uploaded image, temporarily stores the image data, and then proceeds to the next processing step.

[1171] Step 4:

[1172] The server passes the received passport image to the AI-OCR engine and extracts text information from the image. To do this, the image file is first read into the OCR engine and output as text data. The server log records "OCR processing completed."

[1173] Step 5:

[1174] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[1175] Step 6:

[1176] The server passes the translated text data to the review module for review. The server compares the translated text with pre-defined reference data to ensure that they match. For example, it verifies that the passport number and name match the reference data.

[1177] Step 7:

[1178] The server records the results of the review in a log. If necessary, it notifies the user of the results. The server's log records "The review has been completed. The results will be recorded." At this stage, the entire process is complete.

[1179] The above steps enable efficient processing of passports written in foreign languages ​​submitted by users and highly accurate screening, significantly improving the reliability and efficiency of contract procedures.

[1180] Example 1

[1181] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1182] Conventional passport inspection systems lack sufficient automation for character recognition and translation of passports written in foreign languages, resulting in time-consuming and labor-intensive processes. There was also room for improvement in the accuracy and efficiency of inspections. This created a growing need for a system that could quickly and accurately extract passport text data, automatically translate it, and inspect it. Furthermore, there was a need for detailed log management to ensure transparency and traceability of processing.

[1183] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1184] In this invention, the server includes a means for taking a passport image using a terminal and uploading it to the server, a means for processing the received passport image with an optical character recognition engine to extract characters as text data, a means for translating the extracted text data into a specified language using a translation engine, a means for comparing the translated text data with preset standards and reviewing it, and a means for recording all processing steps in detail in a log and saving it for audit purposes. This makes it possible to efficiently and accurately recognize, translate, and review passports written in foreign languages, thereby smoothly progressing contract procedures. Furthermore, log management ensures system transparency and traceability, improving reliability.

[1185] A "terminal" is an electronic device used by a user, such as a mobile phone, smartphone, or tablet, that has a camera function.

[1186] A "server" is a computer system that receives and processes data from terminals via a network, and analyzes and reviews it using various engines.

[1187] "Passport image" is a photograph of a travel document taken by a user with the camera on the terminal, and is image data used for various inspections.

[1188] An "optical character recognition engine (OCR engine)" is a general term for software that detects character information from image data and converts it into text data.

[1189] "Text data" is a data format that includes character information extracted by an OCR engine, and is the content of a document recognized as a string of characters.

[1190] A "translation engine" is software or a service for translating strings from one language to another.

[1191] "Criteria" are pre-defined evaluation criteria or conditions used when reviewing text data.

[1192] "Review" is the process of comparing the extracted and translated text data with standards to confirm matches.

[1193] A "log" is data that describes the work history and results recorded at each processing step of the system.

[1194] "Stored for audit" means storing processing history and results in a secure location for future verification and troubleshooting.

[1195] MODE FOR CARRYING OUT THE INVENTION

[1196] This invention relates to a system that analyzes passport images presented by foreigners, translates their contents, and examines them. This system converts passport images acquired by users into text data using AI-OCR technology, and then translates and examines the data, enabling smooth contract procedures for mobile phones and other devices.

[1197] Hardware and Software Configuration

[1198] The hardware used includes a terminal (such as a smartphone or tablet) and a server. The terminal has a camera function that the user uses to take a passport image.

[1199] The software consists of the following:

[1200] 1. Passport Image Capture Module:

[1201] The user takes a picture of the passport using the device's camera and sends it to the server using a dedicated upload application.

[1202] 2. Receiving and OCR module:

[1203] The server saves the received image files in a specific folder and extracts the text information using an AI-OCR engine, such as the Google Cloud Vision API.

[1204] 3. Translation Module:

[1205] The server sends the text data generated by OCR to a translation engine (such as Google Translate API) and translates it into the specified language.

[1206] 4. Review Module:

[1207] The server reviews the translated text data against pre-set criteria and verifies necessary information such as passport number and name.

[1208] 5. Log Management Module:

[1209] The server will log all transaction results in detail and store audit data to ensure transaction traceability.

[1210] Specific examples

[1211] The user takes a photo of their passport on their device and sends it to the server using a dedicated upload application. The message displayed on the device is "Uploading image to server," and after sending is complete, the message "Upload completed" is displayed.

[1212] The server passes the received image file to the AI-OCR engine for processing. For example, it logs a message saying, "OCR processing completed. Extracted text displayed."

[1213] The server translates the extracted text using the translation module, and the log records "Text translation completed."

[1214] The server evaluates the translated text in the review module and confirms the result. The log will say "Review completed. Recording result."

[1215] Prompt Sentence Examples

[1216] Here are some example prompts for the generative AI model:

[1217] 1. Prompt:

[1218] Upload passport images and create a program that uses AI-OCR and a translation engine to examine the contents of foreign passports.

[1219] 2. Examples of prompts:

[1220] Build a system that takes a photo of a foreigner's passport with a smartphone camera and uploads it to a server, which then extracts text using AI-OCR and translates it using the Google Translate API, and then automatically reviews the passport contents based on that.

[1221] In this way, by clearly specifying the specific processing steps and the hardware and software to be used, it is possible to provide a system that can efficiently process passport contents written in a foreign language and carry out contract procedures smoothly.

[1222] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1223] Program processing flow

[1224] Step 1: Capture and upload a passport image

[1225] Input: Passport image taken by the user using the device camera

[1226] Output: Image file uploaded to the server

[1227] 1. The user launches the camera application on the device.

[1228] 2. The user uses the camera application to take an image containing the entire passport.

[1229] 3. The device displays an interface for uploading the captured images to the server using a dedicated application.

[1230] 4. The user taps the "Upload image" button, and the device sends the image file to the specified server URL. For example, a message appears saying "Uploading image to server."

[1231] 5. Once the image upload is complete, the device will display "Upload complete."

[1232] Step 2: Receiving images and extracting text data using OCR

[1233] Input: Passport image file uploaded to the server

[1234] Output: Text data extracted by OCR

[1235] 1. The server saves the uploaded image files in a specific folder.

[1236] 2. The server passes the saved image file to the AI-OCR engine, which uses the Google Cloud Vision API or similar.

[1237] 3. The AI-OCR engine analyzes the text information in the image and extracts text data such as passport number, name, and place of birth.

[1238] 4. The server temporarily stores the extracted text data in an internal database.

[1239] 5. The processing log will record "OCR processing completed. Extracted text: [Extracted text]".

[1240] Step 3: Translating the text data

[1241] Input: Text data extracted by OCR

[1242] Output: Text data translated by the translation engine

[1243] 1. The server reads the temporarily stored text data and connects to a translation engine (such as Google Translate API).

[1244] 2. The server passes the text data to the translation engine and requests translation into the specified language.

[1245] 3. The translation engine translates the text data into the specified language and returns the translated text data to the server.

[1246] 4. The server receives the translation results and stores them in memory or a database.

[1247] 5. Record the following in the processing log: "Text translation completed. Translation result: [translated text]."

[1248] Step 4: Translation review

[1249] Input: Translated text data

[1250] Output: Review results

[1251] 1. The server reads the pre-defined review criteria from the database.

[1252] 2. The server compares the translation data with the review criteria and confirms a match.

[1253] 3. For example, checking that translated passport numbers are in a valid format and names follow a specific format.

[1254] 4. The server generates the review results and records them in the database.

[1255] 5. Record "Review completed. Result: [Review result]" in the processing log.

[1256] Step 5: Log Management and Auditing

[1257] Input: Execution results and status data for each processing step

[1258] Output: Detailed log files and audit data

[1259] 1. The server records all processing results and times in a log file for each step of image reception, OCR processing, translation processing, and review.

[1260] 2. The server stores the status (success / failure) and detailed error message for each operation.

[1261] 3. The server will regularly back up audit log data and store it in secure storage.

[1262] 4. The server uses these logs for future audits and troubleshooting.

[1263] 5. Record "Log management and audit data storage completed" in the processing log.

[1264] This enables the system to efficiently and accurately analyze passports written in foreign languages, facilitating smooth contract procedures.

[1265] (Application example 1)

[1266] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1267] Conventional identity verification systems using passport information have difficulty handling passports written in multiple languages, making accurate identity verification difficult. Furthermore, because real-time processing was not possible, the verification process took time, resulting in poor user convenience. Furthermore, the lack of traceability and transparency in the process made auditing and troubleshooting difficult.

[1268] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1269] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for reviewing the translated text data, means for taking a passport image with a smart device and processing it in real time, means for verifying the identity of the person by comparing the translated text data with the reservation system, and means for recording all processing steps in a log. This enables accurate real-time identity verification in multiple languages, improving user convenience. It also ensures traceability and transparency of the process, facilitating audits and troubleshooting.

[1270] The "means for receiving a passport image" is a combination of hardware and software that allows a user to take an image of their passport and send the image data to a server.

[1271] The "means for extracting characters from a received passport image as text data" is a system that includes a process of analyzing a received passport image, extracting character information using optical character recognition technology, and converting it into text data.

[1272] "Means for translating extracted text data" refers to software and algorithms for translating the text data extracted by optical character recognition technology into another specified language, such as by using an online translation service or a translation API.

[1273] The "means for reviewing translated text data" refers to a system that structures translated text data and reviews it by comparing it with pre-established standards or databases.

[1274] "Means for taking passport images using a smart device and processing them in real time" refers to hardware and software that allows a passport image to be taken using a mobile device such as a smartphone or tablet, and then immediately sends the image to a server to begin analysis.

[1275] "Means for verifying identity by comparing translated text data with the reservation system" refers to a system that compares translated passport information with the database of the existing reservation system to confirm a match and verify that the user is a legitimate person making a reservation.

[1276] "Means for logging all processing steps" refers to a system that records in detail all processing steps, including receipt, OCR processing, translation, and review, and saves the log data. This ensures traceability and transparency of the process.

[1277] MODE FOR CARRYING OUT THE INVENTION

[1278] The following describes in detail the mode for carrying out this invention. This system is designed to verify the identity of foreign tourists using passport information when they use an automated driving vehicle. The system is composed of the following main components:

[1279] Key Elements

[1280] 1. Passport image capture function

[1281] The user takes a photo of the passport using a smart device (smartphone, tablet, etc.), and the image is uploaded to the server as is.

[1282] 2. Real-time OCR processing

[1283] The server processes the received passport image using an optical character recognition (OCR) engine (e.g., Tesseract OCR) and converts the character information in the image into text data.

[1284] 3. Real-time translation function

[1285] The server translates the text data extracted by OCR into the specified language using an automatic translation engine (e.g., Google Translate API).

[1286] 4. Identity Verification

[1287] The server compares the translated text data with the data in the reservation system to verify that the user is a legitimate user.

[1288] 5. Data log management

[1289] The server logs all processing steps in detail and stores audit data to ensure traceability and transparency of the process.

[1290] Hardware and Software Configuration

[1291] The specific hardware and software used are shown below.

[1292] Smart Devices

[1293] Users take a passport photo using a smart device (smartphone or tablet) and upload the image to the server.

[1294] server

[1295] The following software is installed on the server:

[1296] Optical Character Recognition Engine: Tesseract OCR

[1297] Machine translation engine: Google Translate API

[1298] Database system: SQLite or other database system

[1299] Log management software: ElasticSearch, etc.

[1300] Example of operation

[1301] As an example, consider a scenario where a foreign tourist boards an autonomous vehicle. The tourist uses a smart device to take a photo of their passport. The image data is sent to a server in real time and converted into text data using OCR technology. The text data is translated using the Google Translate API and matched with data from the reservation system. Finally, all processing steps are logged to enable future audits and troubleshooting.

[1302] Example prompt sentence:

[1303] Passport authentication process in autonomous vehicle boarding verification system:

[1304] 1. Travelers capture a passport image with their smartphone.

[1305] 2. Extract text data from images using an OCR engine.

[1306] 3. Translate the extracted text into Japanese using the Google Translate API.

[1307] 4. The translation results are compared with the ride reservation information.

[1308] example:

[1309] Take a picture of your passport and start the OCR process. The process is complete. Your passport information has been converted to text.

[1310] The OCR extracted text was then translated to "Hello." The translated text was then matched against the reservation system to verify the identity of the person.

[1311] In this way, this invention will streamline the identity verification process for foreign tourists when using self-driving vehicles, enabling accurate verification in real time.

[1312] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1313] Step 1:

[1314] The user takes a picture of their passport with a smart device (smartphone or tablet) and obtains the image data. Specifically, the user launches the camera app and takes a picture of the passport. The input is the image of the passport taken by the user, and the output is the image data.

[1315] Step 2:

[1316] The terminal uploads the acquired passport image to the server. The terminal has a built-in program that sends the captured image to a specified server URL, which sends the image data to the server in real time. The input is the passport image data, and the output is the image data sent to the server.

[1317] Step 3:

[1318] The server inputs the received passport image into an optical character recognition (OCR) engine to extract text information from the image. Specifically, it uses Tesseract OCR to convert the text information in the image into text data. The input is the passport image data, and the output is the extracted text data.

[1319] Step 4:

[1320] The server passes the text data extracted by OCR to the translation engine and translates it into the specified language. Specifically, the text data is translated using the Google Translate API. The input is the text data extracted by OCR, and the output is the translated text data.

[1321] Step 5:

[1322] The server checks the translated text against the reservation system to verify that the user is a valid reservation holder. Specifically, it performs a database query to verify a match against the reservation information. The input is the translated text and the reservation system data, and the output is the identity verification result.

[1323] Step 6:

[1324] The server records all processing steps in a log and saves the audit data. Specifically, it records the details of the processing performed at each step and the results, and saves them in log management software such as ElasticSearch. The input is the result data of each processing step, and the output is the saved log data.

[1325] This processing flow automates the entire process, from taking passport photos to identity verification and log management, ensuring smooth identity verification for foreign tourists when using self-driving vehicles.

[1326] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1327] System Overview

[1328] This invention is a system that analyzes passport images presented by foreigners when signing contracts for mobile phones and other devices, translates the contents, and reviews them. It also combines an emotion engine that recognizes the user's emotions. This system converts passport images taken by users into text data using AI-OCR technology, which then translates the data for accurate review. It also recognizes the user's emotions, records the user's emotional state during the review process, and provides feedback as needed.

[1329] System configuration

[1330] 1. Passport Image Capture Module

[1331] The user takes a photo of their passport using their handheld device. The device also uses a camera and microphone to capture the image and to recognize the user's emotions. This data is then uploaded to the server.

[1332] 2. Receiving and OCR module

[1333] The server processes the received image file and emotion data, and uses an AI-OCR engine to extract text data from the passport image.

[1334] 3. Translation Module

[1335] The server passes the extracted text to a translation engine for translation into a specific language, while simultaneously analyzing the user's emotional data and recording the user's emotional state during the review process.

[1336] 4. Review Module

[1337] The server then compares the translated text with the necessary information, such as passport number and name, to verify it against the screening criteria. Furthermore, an emotion engine evaluates the user's emotional state and provides feedback to ensure the fairness of the screening process and the user's sense of security.

[1338] 5. Log Management Module

[1339] The server logs all processing results and emotion data and stores audit data to ensure processing traceability.

[1340] Program processing

[1341] Capture and upload a passport image

[1342] The user takes a passport photo with the device's camera and records their own face and voice to obtain emotion data, which is then uploaded to the server.

[1343] Extracting text data using OCR

[1344] The server processes the received passport image with an AI-OCR engine, extracts text information from the image, and simultaneously analyzes the received emotional data to obtain the user's emotional state. For example, it determines whether the user is relaxed or anxious.

[1345] Translation processing and sentiment analysis

[1346] The server passes the text data extracted by OCR to a translation engine, which translates it into the specified language (e.g., English). In parallel, the emotion engine analyzes the user's emotion data and detects significant emotional changes.

[1347] Review and feedback of input data

[1348] The server then checks the translated text against pre-defined criteria. To ensure fairness in the review, the system also evaluates the user's emotional state and provides appropriate feedback. For example, if the user is feeling anxious, the system can send a reassuring message.

[1349] Logging and Auditing

[1350] The server records detailed logs of all processing steps and the corresponding emotion data. To ensure traceability and transparency of the system, an audit log is kept, which can be used for later review and troubleshooting.

[1351] Specific examples

[1352] The user takes a photo of their passport on their device and uploads it to the server, while simultaneously capturing a photo of their face to obtain emotional data. The device displays "Uploading image to server," and once the upload is complete, it displays "Upload completed."

[1353] The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and simultaneously performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[1354] The server uses a translation module to translate the extracted text and analyze the sentiment data to obtain insights necessary for review. The log records, "Text translation and sentiment analysis completed."

[1355] The server reviews the translated text and confirms the results while assessing the user's emotional state. It provides feedback to the user as needed. The log states, "Review completed. Recording results and feedback."

[1356] In this way, the present invention can efficiently process passport contents written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[1357] The processing flow will be explained below.

[1358] Step 1:

[1359] The user takes a picture of their passport using their device. The device's camera function is activated and the entire passport is captured clearly. At the same time, the user's face and voice are also recorded, and emotional data is acquired. This image and emotional data are then stored on the device.

[1360] Step 2:

[1361] The device uploads the passport image and emotion data it has taken to the specified server URL. The device then sends the image file (e.g., passport.jpg) and emotion data to the server using an HTTP POST request. During this process, the device displays a message to the user saying, "Sending image and emotion data to server."

[1362] Step 3:

[1363] The server receives the uploaded image and emotion data. The server temporarily stores this data and proceeds to the next processing step. The server log records "Passport image and emotion data received."

[1364] Step 4:

[1365] The server passes the received passport image to the AI-OCR engine, which extracts text information from the image. The OCR engine analyzes the image file and outputs it as text data. At the same time, the emotion engine analyzes the received emotion data. The server log records, "OCR processing and emotion analysis completed."

[1366] Step 5:

[1367] The server passes the text data extracted by the OCR engine to the translation engine, which translates it into the specified language (e.g., English). This step uses an external translation service such as Google Translate API. The server log records "Text translation completed."

[1368] Step 6:

[1369] The server obtains the text data translated by the translation engine and passes it to the review module. The review module compares the translated text with pre-set reference data to confirm whether they match. At the same time, it evaluates the emotional data analyzed by the emotion engine to ensure the fairness of the review process. The server log records "Review and emotion evaluation completed."

[1370] Step 7:

[1371] The server provides feedback to the user based on the review results and emotional data. For example, if the user is feeling anxious, it will send a reassuring message. The user can check the results and feedback on their device. The server log will record "Feedback has been sent to the user."

[1372] Step 8:

[1373] The server records all processing results and emotion data in a detailed log and saves it as audit data. This log is used for future review and troubleshooting. The server log will record "All processing has been logged."

[1374] This series of steps allows for efficient processing of passports submitted by users written in foreign languages ​​and highly accurate screening. Furthermore, by using an emotion engine, a fair screening process is realized that takes into account the user's emotional state. This significantly improves the reliability and efficiency of contract procedures.

[1375] Example 2

[1376] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1377] When foreigners apply for a contract for a mobile phone or other device, the details of their passport must be accurately analyzed and reviewed. However, it is difficult to process passport details written in a foreign language quickly and accurately. Furthermore, there is a lack of a system to alleviate the anxiety and stress users may feel during the process. Furthermore, traceable log management is necessary to ensure the fairness and transparency of the process.

[1378] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for acquiring emotional data from the user, means for analyzing the acquired emotional data, means for reviewing the translated text data, means for providing feedback based on the review results and the emotional data, and means for recording the processing steps and the emotional data in a log. This enables a fair review process that takes into account the emotional state of the user while efficiently processing the contents of a passport written in a foreign language, and highly transparent log management.

[1379] The "means for receiving a passport image" is a function for transmitting image data of a passport taken by a user using a terminal to a server, and for the server to receive the image data.

[1380] The "means for extracting characters as text data from a received passport image" is a function that uses optical character recognition (OCR) technology to extract character information from a received passport image as digital text data.

[1381] The "means for translating extracted text data" is a function for converting text data extracted by OCR into a specified language using a multilingual translation engine.

[1382] The "means for acquiring emotional data from the user" is a function for detecting and acquiring the emotional state of the user using the user's facial image and voice data.

[1383] The "means for analyzing acquired emotional data" is a function for analyzing acquired emotional data and grasping the emotions (relaxation, tension, anxiety, etc.) that the user is experiencing.

[1384] The "means for reviewing translated text data" refers to a function for comparing the translated text data with pre-established review criteria to confirm its accuracy and suitability.

[1385] "Means for providing feedback based on the screening results and emotional data" is a function that provides appropriate feedback to the user (such as a message that gives a sense of security or instructions on the next steps) based on the screening results and emotional data.

[1386] The "means for logging processing steps and emotional data" refers to a function that records all processing steps and the corresponding emotional data in detail as a log and saves it for future audits and troubleshooting.

[1387] The present invention is a system used by foreigners when completing procedures such as signing a mobile phone contract, and combines passport image analysis, translation, and user emotion recognition. Details for implementing this system are described below.

[1388] System configuration

[1389] 1. Passport Image Capture Module

[1390] The user takes a photo of their passport using the camera on their device. The system also captures emotional data, such as the user's face and voice, which are then encoded and uploaded to the server.

[1391] 2. Receiving and OCR module

[1392] The server receives the passport image and emotion data sent by the user. It then uses an AI-OCR engine (e.g., Google Cloud Vision API) to extract text data from the received passport image. In parallel, the emotion data is also analyzed to understand the user's emotional state.

[1393] 3. Translation Module

[1394] The server passes the text data extracted by the AI-OCR engine to a translation engine (e.g., Google Translate API) and translates it into the specified language (e.g., English). At the same time, it also uses an emotion engine to analyze emotion data and records changes in the user's emotional state.

[1395] 4. Review Module

[1396] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, issue date, expiration date, etc.) to verify accuracy and consistency. Furthermore, it evaluates the emotional data analyzed by the emotion engine and provides feedback to the user to maintain a fair review process.

[1397] 5. Log Management Module

[1398] The server records and stores detailed logs of all processing steps and the corresponding emotion data, ensuring transparency and traceability of the system and allowing for future review and troubleshooting.

[1399] Example

[1400] 1. The user takes a photo of their passport on their device and uploads it to the server, while simultaneously recording their facial image and voice to obtain emotional data. The device displays "Uploading image to server" and notifies them that "Upload completed" when the upload is complete.

[1401] 2. The server receives the image and emotion data, extracts the text information from the passport through the OCR module, and performs emotion analysis. The log records "OCR processing and emotion analysis completed."

[1402] 3. The server uses the translation module to translate the extracted text and analyze the sentiment data to obtain insights needed for review. The log records, "Text translation and sentiment analysis completed."

[1403] 4. The server reviews the translated text, assesses the user's emotional state, and confirms the results. It provides feedback to the user if necessary. The log records, "Review completed. Feedback has been sent to the user."

[1404] 5. The server records all processing steps and emotion data in a detailed log and stores it for future auditing. The log will state, "All processing steps completed. Log data stored."

[1405] Prompt Sentence Examples

[1406] The following prompt sentences can be input to the generative AI model:

[1407] "Please build a system that analyzes an image of my passport, translates and reviews the contents, and simultaneously assesses my emotional state. Please explain the specific steps and technologies used."

[1408] In this way, the embodiments of the invention effectively process the contents of passports written in foreign languages ​​and realize a fair screening process that takes into account the emotional state of the user, thereby significantly improving the reliability and efficiency of contract procedures.

[1409] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1410] Step 1: Taking a passport photo and acquiring emotion data

[1411] The user takes a passport image using the camera on their device. At the same time, emotional data such as their face and voice are captured. Specifically, the user captures this data by pressing the capture button using a camera and microphone with facial recognition capabilities. The device encodes this data and uploads it to the server. The input is the image captured by the device camera and the recorded voice data, and the output is a data packet containing these uploaded to the server.

[1412] Step 2: Receiving and storing data

[1413] The server receives data packets sent by the user. The server stores the passport image file and emotion data (face image and voice data) in its respective data storage. The input is a data packet containing the image and emotion data from the user terminal, and the output is the passport image file and emotion data stored in the data storage.

[1414] Step 3: Extract text data using OCR

[1415] The server inputs the saved passport image into an AI-OCR engine (for example, Google Cloud Vision API) and extracts text information from the image. Specifically, the passport image data is passed to the engine, and text data such as the name and passport number is extracted from it. The input is the saved passport image file, and the output is the extracted text data.

[1416] Step 4: Analyze the sentiment data

[1417] The server inputs the stored facial image and voice data into an emotion engine to analyze the user's emotional state. Specifically, it uses facial expression recognition and voice analysis technology to evaluate the user's emotions, such as whether they are relaxed or anxious. The input is the stored facial image and voice data, and the output is the analyzed emotional state data.

[1418] Step 5: Translating the text data

[1419] The server passes the text data extracted by OCR to a translation engine (e.g., Google Translate API) to translate it into the specified language. For example, translating Japanese text into English. The input is the extracted text data, and the output is the translated text data.

[1420] Step 6: Review and evaluate the translation data

[1421] The server compares the translated text data with pre-defined criteria (e.g., passport number, name, expiration date, etc.) to verify its accuracy and suitability. At the same time, it evaluates the emotion data to ensure that the review is fair. The input is the translated text data and the analyzed emotion data, and the output is the review result.

[1422] Step 7: Provide feedback to users

[1423] The server provides appropriate feedback to the user based on the evaluation result and emotion data. For example, if the user feels anxious, it sends a message such as "Everything is fine. Don't worry." The input is the evaluation result and emotion data, and the output is the feedback message sent to the user.

[1424] Step 8: Logging and Auditing

[1425] The server records and stores detailed logs of all processing steps and corresponding emotion data for later review and troubleshooting. The inputs are each processing step and its output data, and the output is the stored log data.

[1426] (Application example 2)

[1427] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1428] It is difficult to efficiently and accurately verify the identity of foreign users of self-driving vehicles, and there are also lack of measures to alleviate anxiety caused by language differences and cultural backgrounds. Therefore, it is necessary to provide a sense of security to foreign users in self-driving vehicles by quickly and accurately authenticating them and at the same time taking into account their emotional state.

[1429] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1430] In this invention, the server includes means for receiving a passport image, means for extracting characters from the received passport image as text data, means for translating the extracted text data, means for examining the translated text data, an emotion engine for recognizing a user's emotion, means for recording the user's emotional state and providing feedback as necessary, and means for processing passport recognition and the user's emotional state within the self-driving vehicle. This makes it possible to quickly and accurately verify the identity of foreign users of self-driving vehicles and provide feedback according to their emotional state.

[1431] "Means for receiving a passport image" refers to a device or method that has the function of taking or scanning an image of the passport presented by the user and transmitting it to the system.

[1432] The "means for extracting characters as text data" refers to a device or method that has the function of recognizing character information from a received passport image and converting it into digital text data.

[1433] The "means for translating extracted text data" refers to a device or method that has the function of translating text data obtained by OCR (Optical Character Recognition) into a different language.

[1434] "Means for reviewing translated text data" means a device or method that has the function of checking and verifying translated text data against pre-established criteria.

[1435] An "emotion engine that recognizes the user's emotions" is a device or software that has the function of analyzing the user's facial expressions, voice, etc. and determining their emotional state.

[1436] A "means for recording a user's emotional state and providing feedback as needed" is a device or method capable of recording a user's emotional state and providing reassuring messages or other feedback based on that data.

[1437] "Means for recognizing passports and processing the emotional state of users within an autonomous vehicle" refers to a device or method that is a system installed in an autonomous vehicle and has the function of recognizing the passport information of foreign users and analyzing the emotional state of the users to respond appropriately.

[1438] MODE FOR CARRYING OUT THE INVENTION

[1439] System configuration

[1440] This invention is a system for efficiently and accurately implementing passport-based authentication procedures for foreign users in automated driving vehicles. The system is composed of the following main components:

[1441] 1. Passport Image Capture Module

[1442] When a user gets into an autonomous vehicle, the device uses a camera installed inside the vehicle to take an image of the user's passport, and also captures video of the user's face to obtain emotional data.

[1443] 2. Data transmission module

[1444] The device transmits the acquired passport image and emotion data to a server via an internet connection.

[1445] 3. OCR and Translation Module

[1446] The server processes the received passport image using an AI-OCR engine to extract text information from the image, and then passes the extracted text data to a translation engine (e.g., Google Translate) to translate it into a specific language.

[1447] 4. Sentiment Analysis Module

[1448] The server analyzes the received emotion data and determines the user's emotional state using software such as the Facial Recognition Library.

[1449] 5. Review and Feedback Module

[1450] The server then authenticates the user based on the translated text data, comparing it with pre-defined criteria, while simultaneously recording the user's emotional state and sending reassuring feedback to the device as needed.

[1451] Program processing

[1452] The processing of each module is carried out as follows.

[1453] Passport image capture: The device takes a passport image using the in-car camera and simultaneously captures a video of the user's face. This data is temporarily stored on the device.

[1454] Data transmission: The device transmits the stored passport image and facial video to a server via the Internet.

[1455] OCR and translation: The server uses OpenCV and Pytesseract to perform OCR on the received passport image and extract text data, which is then translated into the specified language using the Google Translate API.

[1456] Emotion Analysis: The server analyzes the captured facial video using the Facial Recognition Library to determine the user's emotional state. This data is used as key insight into the review process.

[1457] Verification and feedback: The server performs authentication based on the translated text data, comparing it with pre-defined criteria. Depending on the user's emotional state, it sends appropriate feedback messages (e.g., "The process is going smoothly" or "Don't worry, please wait a moment for the process") to the terminal and displays them to the user.

[1458] Specific examples

[1459] As a concrete example, consider the following scenario.

[1460] 1. A user enters an autonomous vehicle and takes a photo of their passport using the device. The device displays "Sending image."

[1461] 2. The device sends the passport image and facial video to the server.

[1462] 3. The server processes the images with OCR, translates the text data, and analyzes the emotions in the facial images.

[1463] 4. The server judges the results of the evaluation and sends feedback to the device according to the user's emotional state.

[1464] 5. The device will display "The process is going smoothly" or "Don't worry, the process will take a moment."

[1465] Example prompt for a generative AI model:

[1466] The user takes a photo of their passport on the tablet and the message "Sending image" appears. The server then processes the image with OCR, translates it, and performs sentiment analysis, displaying feedback based on the user's emotional state. For example, "The process is going smoothly" or "Don't worry, please wait a moment while the process is completed."

[1467] In this way, the present invention makes it possible to quickly and accurately verify the identity of foreign users in self-driving vehicles and provide appropriate feedback according to their emotional state.

[1468] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1469] Program processing steps

[1470] Step 1:

[1471] The device is a camera installed in an autonomous vehicle that captures the user's passport image and facial video. The input is the passport image and the user's facial video, which are temporarily stored on the device. Specifically, the device's camera app is launched, the user is instructed to show their passport, and the image is taken by pressing the shutter button.

[1472] Step 2:

[1473] The device sends the captured passport image and facial video to the server. The input is the passport image and facial video stored on the device, and the output is data sent over the Internet. Specifically, the device's network module is used to send an HTTP POST request to the specified server URL.

[1474] Step 3:

[1475] The server extracts text data from the received passport image using an AI-OCR engine. The input is the passport image, and the output is the extracted text data. Specifically, the image is read using OpenCV, and text information is extracted from the image using Pytesseract.

[1476] Step 4:

[1477] The server passes the extracted text data to a translation engine for translation into a specific language. The input is OCR-processed text data, and the output is translated text data. Specifically, the text data is sent to the Google Translate API and the translated results are received.

[1478] Step 5:

[1479] The server analyzes the received facial video using an emotion analysis module to determine the user's emotional state. The input is the user's facial video, and the output is the analyzed emotional data. Specifically, the server processes the facial video using the Facial Recognition Library and classifies the emotional state.

[1480] Step 6:

[1481] The server compares the translated text data with the authentication criteria to confirm a match. At the same time, it records the user's emotional state and sends feedback as needed. The input is the translated text data and emotional data, and the output is the authentication result and a feedback message based on the emotion. Specifically, it compares the data with a pre-configured authentication criteria database to verify whether the user meets the authentication criteria, and generates a feedback message along with the authentication result.

[1482] Step 7:

[1483] The terminal displays the feedback message received from the server. The input is the feedback message sent from the server, and the output is the message displayed on the terminal display. As a specific operation, the message is displayed using a UI component that displays the message on the terminal display.

[1484] Through these processing steps, the system can quickly and accurately verify the identity of foreign users in autonomous vehicles and provide appropriate feedback according to their emotional state.

[1485] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1486] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1487] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1488] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1489] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1490] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1491] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1492] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1493] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1494] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1495] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1496] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1497] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1498] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1499] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1500] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1501] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1502] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1503] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1504] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1505] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1506] The following is further disclosed regarding the above embodiment.

[1507] (Claim 1)

[1508] means for receiving an image of a passport;

[1509] A means for extracting characters from the received passport image as text data;

[1510] means for translating the extracted text data;

[1511] A means for reviewing the translated text data;

[1512] A system including:

[1513] (Claim 2)

[1514] 10. The system of claim 1, wherein the received passport image is input into an optical character recognition engine to extract text data.

[1515] (Claim 3)

[1516] 10. The system of claim 1, wherein the translated text data is compared with pre-specified reference data to confirm a match.

[1517] "Example 1"

[1518] (Claim 1)

[1519] A means for taking an image of the passport by the terminal and uploading it to a server;

[1520] A means for processing the received passport image with an optical character recognition engine and extracting characters as text data;

[1521] A means for translating the extracted text data into a specified language using a translation engine;

[1522] a means for reviewing the translated text data by comparing it with pre-defined criteria;

[1523] A means to log all processing steps in detail and store them for audit purposes;

[1524] A system including:

[1525] (Claim 2)

[1526] 10. The system of claim 1, wherein the uploaded passport image is stored and input into an optical character recognition engine.

[1527] (Claim 3)

[1528] 10. The system of claim 1, wherein the translated text data is matched against reference data to confirm a match.

[1529] "Application Example 1"

[1530] (Claim 1)

[1531] means for receiving an image of a passport;

[1532] A means for extracting characters from the received passport image as text data;

[1533] means for translating the extracted text data;

[1534] A means for reviewing the translated text data;

[1535] A means to take passport images using a smart device and process them in real time;

[1536] A means for verifying the identity of the person by comparing the translated text data with the reservation system;

[1537] a means of logging all processing steps;

[1538] A system including:

[1539] (Claim 2)

[1540] 10. The system of claim 1, wherein the received passport image is input into an optical character recognition engine to extract text data.

[1541] (Claim 3)

[1542] 10. The system of claim 1, wherein the translated text data is compared with pre-specified reference data to confirm a match.

[1543] (Claim 4)

[1544] The system of claim 1, wherein passport images are captured and processed in real time using a smart device.

[1545] (Claim 5)

[1546] 2. The system of claim 1, wherein the translated text data is compared with a reservation system to verify the identity of the user.

[1547] (Claim 6)

[1548] 10. The system of claim 1, wherein all processing steps are logged.

[1549] "Example 2: Combining Emotion Engines"

[1550] (Claim 1)

[1551] means for receiving an image of a passport;

[1552] A means for extracting characters from the received passport image as text data;

[1553] means for translating the extracted text data;

[1554] means for acquiring emotion data from a user;

[1555] A means for analyzing the acquired emotion data;

[1556] A means for reviewing the translated text data;

[1557] a means of providing feedback based on the review results and sentiment data;

[1558] means for logging processing steps and emotion data;

[1559] A system including:

[1560] (Claim 2)

[1561] 10. The system of claim 1, wherein the received passport image is input into an optical character recognition engine to extract text data.

[1562] (Claim 3)

[1563] 10. The system of claim 1, wherein the translated text data is compared with pre-specified reference data to confirm a match.

[1564] "Application example 2 when combining emotion engines"

[1565] (Claim 1)

[1566] means for receiving an image of a passport;

[1567] A means for extracting characters from the received passport image as text data;

[1568] means for translating the extracted text data;

[1569] A means for reviewing the translated text data;

[1570] an emotion engine that recognizes the user's emotions;

[1571] means for recording the user's emotional state and providing feedback as needed;

[1572] a means for processing passport recognition and the emotional state of the user within the self-driving vehicle;

[1573] A system including:

[1574] (Claim 2)

[1575] 10. The system of claim 1, wherein the received passport image is input into an optical character recognition engine to extract text data.

[1576] (Claim 3)

[1577] 10. The system of claim 1, wherein the translated text data is compared with pre-specified reference data to confirm a match. [Explanation of symbols]

[1578] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving an image of a passport; A means for extracting characters from the received passport image as text data; means for translating the extracted text data; A means for reviewing the translated text data; A system including:

2. 10. The system of claim 1, wherein the received passport image is input to an optical character recognition engine to extract text data.

3. 10. The system of claim 1, wherein the translated text data is compared with pre-specified reference data to confirm a match.

Images