system

Abstract

We provide the system. [Solution] A means for analyzing the visible seal impression contained in the application form using an image processing device, identifying the type of the seal impression, and converting the symbols within the seal impression into character data, Means for recording the aforementioned character data in an information storage device that stores the data for each organization, A means for comparing the seal impression on a newly submitted application form with the stored information in the information storage device and determining whether the seal is appropriate according to predetermined standards, Means for outputting the aforementioned determination result to a display device, A means of automatically verifying the validity of a seal impression by photographing the visible seal impression, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, in the business of verifying the seals on applications submitted by corporations, it has been necessary to manually visually check the types and characters of the seals, which has been laborious and time-consuming. Furthermore, since the checks are performed based on different rules for each service type and business type, the verification work requires high expertise and proficiency, and there is a demand for improving the efficiency of operations.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides a means for identifying the type of seal impression and converting the characters within the seal impression into text data by analyzing the seal impression contained in the application form using an image processing device. The invention also includes a means for recording the text data in a database stored for each company, comparing the seal impression of a newly submitted application form with the stored data in the database, and determining whether the seal impression is appropriate according to predetermined standards. Furthermore, the invention aims to improve the efficiency of the seal impression verification process by displaying the determination result on an output device and notifying the user whether a visual inspection is necessary.

[0006] "Seal impression" refers to the shape and characters of a seal that appear on paper when it is stamped on a document such as an application form.

[0007] An "image processing device" refers to a device or computer program that analyzes and processes digital images and extracts specific information.

[0008] "Text data" refers to character information stored in a digital format that can be processed by a computer.

[0009] A "database" is a structured system for efficiently storing, searching, and managing a collection of information.

[0010] "Storing information on a company-by-company basis" refers to managing and storing information related to each company individually.

[0011] "Means of judgment" refers to a device or program that has the function of processing data based on specific criteria and deriving results.

[0012] An "output device" refers to a device that displays processed information visually or in other formats.

[0013] "User" refers to any person who operates or uses this system.

[0014] "Whether or not a visual inspection is necessary" refers to determining whether or not it is necessary to directly verify the stamping process with human eyes.

Brief Description of the Drawings

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. <� [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] Shows an emotion map to which multiple emotions are mapped. [Figure 10] Shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the 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.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0029] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention is a system designed to streamline the process of stamping application forms by specific industries and companies. The system automatically identifies the type and content of the stamp through image analysis of the stamp impression, reducing the need for manual visual verification.

[0037] First, the user scans the application form submitted by the company as digital data and uploads it to the server. This allows the application form data to be imported into the system. The server processes the received application form data and uses an image processing device to extract the stamped portion.

[0038] Once a stamped image is extracted, the server sends it to a generating AI model for detailed analysis. The generating AI model converts the shape and type of the stamp (round, square, etc.) and the characters within the stamp into text data. This text information obtained through analysis is stored in a database as important elements.

[0039] Subsequently, when a new application form is submitted, the server analyzes the application form again and processes the image of the seal impression using an AI model that generates images. The extracted text information is compared with the previously stored data. The server automatically determines the appropriateness of the seal impression based on predetermined criteria and makes a decision based on that result.

[0040] Ultimately, the terminal presents the user with the result of its decision. For example, if the stamp has already been verified, a notification will appear stating that visual inspection is unnecessary. This allows the user to proceed with the verification process quickly and efficiently. This system is expected to automate the stamp verification process and enable the effective use of human resources.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users scan application forms submitted by companies and upload the corresponding digital data to the server. This allows the application form data to be imported into the system.

[0044] Step 2:

[0045] The server processes the received application form data, uses an image processing device to detect the stamped area, and performs cropping. This cropping extracts the image data of the stamp.

[0046] Step 3:

[0047] The server sends the extracted stamped image to the generating AI model and requests analysis. The generating AI model analyzes the shape and type of the stamp, as well as the text information within the stamp impression, and returns it as text data.

[0048] Step 4:

[0049] The server organizes the text data obtained from the generated AI models by company and stores it in a database. This database is then made available for reference during subsequent signature checks.

[0050] Step 5:

[0051] When a new application form is submitted, the server receives the application form again, processes the stamped area as an image, and obtains the text data using a generative AI model.

[0052] Step 6:

[0053] The server compares the stored stamp data in the database with the newly acquired data and determines the legitimacy of the stamp according to the specified rules.

[0054] Step 7:

[0055] The terminal displays the results of the stamping check obtained from the server to the user. If there are no problems with the stamping, the user is notified that visual inspection is not required.

[0056] (Example 1)

[0057] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0058] Traditionally, verifying the authenticity of seals on application forms and other documents has been a time-consuming and labor-intensive process due to the reliance on manual labor. Furthermore, the possibility of human error in the verification process cannot be ruled out. Therefore, there is a need to quickly and automatically determine the appropriateness of seals to improve efficiency and accuracy.

[0059] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0060] In this invention, the server includes means for analyzing the seal impression contained in the application form using an image processing device to identify the shape and type of the seal impression and convert the contents of the seal impression into text data; means for recording the text data in a storage device that stores the data for each organization; and means for analyzing the extracted text data using an artificial intelligence model that generates data and storing the generated information. This makes it possible to automate the process of verifying the seal impression and to make decisions efficiently and accurately.

[0061] An "application form" is an official document submitted to apply for a specific procedure or service.

[0062] An "impression" is the trace of shape or characters left behind when a stamp or seal is pressed onto something.

[0063] An "image processing device" is a system of hardware or software for analyzing, converting, and displaying digital images.

[0064] "Text data" refers to data that represents character information in a digital format.

[0065] An "organization" is a group or institution formed for a specific purpose or activity.

[0066] A "storage device" is hardware or software used to store digital data.

[0067] A "generative artificial intelligence model" is a collection of algorithms built using machine learning and deep learning techniques to analyze, judge, and generate data as input.

[0068] A "display device" is hardware used to present information visually, and usually refers to a screen or monitor.

[0069] This invention is a system for streamlining the process of verifying seals on application forms. Specifically, it is operated through the roles of server, terminal, and user.

[0070] The user first digitizes the application form using a scanner. At this stage, a standard scanning device is used to convert the application form into a PDF or image file (JPEG, PNG, etc.). Next, the user uploads the digitized file to the server. This allows the application data to be imported into the system.

[0071] After receiving the uploaded data, the server analyzes the seal impression portion of the image using an image processing library (e.g., OpenCV). This image processing device recognizes the shape and type of the seal impression and converts the character codes within the impression into digital text data. The converted text data is then stored in a memory device by the server. This stored data plays an important role as it will be used for later comparisons and other purposes.

[0072] Next, the server utilizes a generative AI model to perform a detailed analysis of the extracted text data. The generative AI model uses a deep learning algorithm to analyze the seal impressions and uses the accumulated information to generate new patterns and determine their appropriateness.

[0073] This system significantly automates the stamp verification process. If the stamp is valid, the terminal displays the result to the user, notifying them that further visual verification is unnecessary. This allows users to expedite the verification process and improve overall operational efficiency.

[0074] As a concrete example, consider the application forms used when opening an account at a financial institution such as a bank. By applying this system, it becomes possible to efficiently review the enormous number of application forms on a daily basis.

[0075] Examples of prompt statements are as follows:

[0076] "Please analyze the following stamp image and convert the type of stamp and its contents into text."

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user scans and digitizes the application form. The input is a paper application form, which is converted to a PDF or image file using a scanner. The output is the digitized application form data. This data will be used in the next processing step, so the file format should be standard.

[0080] Step 2:

[0081] Users upload digitized application forms to the server via a dedicated platform. The input is a digital file stored on the user's device. The output is the application form data sent to the server and incorporated into the system. The upload operation is performed using the user interface, and the server accurately receives the file.

[0082] Step 3:

[0083] The server processes the received data using an image processing device. The input is the uploaded application form data (in image or PDF format). An image processing library (e.g., OpenCV) is used to identify and extract the stamped area. The output is the extracted stamped image. This image is used in the next analysis step.

[0084] Step 4:

[0085] The server sends the extracted stamp image to the generation AI model for analysis. The input is image data of the stamp. The generation AI model uses deep learning technology to analyze the shape of the stamp and the content of the characters inside, and generates text data. The output is the analyzed text information. This information is stored in a database for verification.

[0086] Step 5:

[0087] The server compares the generated text data with an existing database. The input consists of newly generated text information and historical records within the database. This allows for data analysis to determine the degree of consistency and appropriateness of the seal impressions. The output is the judgment result regarding the appropriateness of the seal impressions.

[0088] Step 6:

[0089] The terminal displays the results from the server to the user. The input is the decision result sent from the server. The results are visually displayed on the terminal, prompting the user to take the necessary action. The output is a result message presented to the user, which includes information such as "Seal has been confirmed." The user then decides on their next action based on this.

[0090] (Application Example 1)

[0091] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0092] In daily operations, verifying the presence of a seal on a document is a time-consuming and laborious process. This invention aims to efficiently identify the seal impressions on coupons and membership cards in physical stores, reduce the time required for seal verification, and prevent fraudulent use.

[0093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0094] In this invention, the server includes means for analyzing the visible seal impression contained in the application form using an image processing device, identifying the type of seal impression, and converting the symbols within the seal impression into character data; means for recording the character data in an information storage device that stores data for each organization; and means for comparing the seal impression of a newly submitted application form with the stored information in the information storage device and determining whether the seal impression is appropriate according to predetermined standards. This enables automatic recognition and verification of coupons and membership cards in physical stores.

[0095] A "visible impression" is an impression that is imprinted in a form that is visible on paper or a digital screen.

[0096] An "image processing device" is an electronic device used to analyze, convert, and identify captured image data.

[0097] A "symbol" refers to an identifiable character element, such as an alphabet or number, included within the seal impression.

[0098] "Character data" refers to information that represents analyzed symbols in digital format.

[0099] An "information storage device" is a storage system for securely storing digital data over long periods of time.

[0100] "Storing data by organization" refers to a method of individually recording and storing data associated with different groups or corporations.

[0101] "Automatic recognition" is the ability of a machine or software to identify specific patterns or information without human intervention.

[0102] "Means of judgment" refers to a method or process of evaluating whether something is appropriate or not using specific criteria based on the information that has been entered.

[0103] This invention is a system for the automatic recognition and verification of coupons and membership cards within a store. The user uses a smart device to capture a visible imprint of the presented coupon. The captured image data is transmitted to a server in real time.

[0104] The server uses an image processing device to extract visible seal impressions from received images and analyzes the symbols contained within those impressions. A generative AI model is used for this analysis, automatically identifying the type of seal impression and converting the symbols into character data. The converted character data is recorded in information storage devices for each relevant organization.

[0105] Next, the server compares the text data of the newly submitted coupon with information already stored in the information storage device. This comparison determines whether the coupon is valid according to predetermined criteria. The result is immediately output to the terminal's display device and notified to the user. For example, if the coupon is valid, it will display "20% off applied."

[0106] As a concrete example, the generating AI model recognizes and processes a seal impression based on a prompt message such as, "Analyze the seal impression in this image, extract text information, and determine its validity." Based on this prompt message, the AI ​​performs an appropriate analysis, enabling the entire system to operate efficiently.

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The user uses a smart device to capture a visible imprint on the presented coupon. This captured image becomes the input. The captured image data is then sent directly to the server.

[0110] Step 2:

[0111] The server analyzes the received image data using an image processing device. Here, data processing is performed to extract visible seal impressions from the image. The extracted seal impressions become the output, and the process proceeds to the next stage.

[0112] Step 3:

[0113] The server utilizes a generation AI model to analyze the extracted seal impressions. The input is the extracted seal impressions, and it performs data calculations to recognize the symbols contained within the impressions and convert them into character data. This character data becomes the output and is sent to the information storage device.

[0114] Step 4:

[0115] The server records character data in an information storage device and stores it in the database of the relevant organization as needed. The input is converted character data, and the output is recorded data.

[0116] Step 5:

[0117] The system compares the text data of newly submitted coupons with existing data. The server uses predetermined criteria to evaluate the input data and performs data calculations to assess the validity of the coupons. The results of the validity assessment are then output.

[0118] Step 6:

[0119] The server sends the judgment result to the terminal's display device. The input here is the judgment result of the suitability, and the output notified to the user is the display screen. Specifically, if the validity is confirmed, the application of discounts, etc., will be clearly indicated.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] This invention is a system that automates the verification of seals on application forms and provides feedback that takes user emotions into consideration. This system operates by combining image processing technology that identifies the type and characters of the seals with an emotion engine that recognizes user emotions.

[0122] First, the user digitally scans the application form submitted by the company and uploads it to the server. The server receives this data and uses an image processing device to detect and analyze the seal portion of the application form. Here, the shape of the seal and the text information within the seal impression are extracted and stored in a database as text data.

[0123] Next, newly submitted application forms are processed in the same manner and compared with accumulated data to automatically evaluate whether the seal impression conforms to the regulations. The emotion engine analyzes the user's facial expressions and voice when the user checks the results to determine their emotional state. As a result, for example, if the user is tense, the device uses relaxing interfaces and notifications to reduce stress.

[0124] Furthermore, convenience is enhanced by providing quick and simple feedback to users who are fully satisfied. This system not only streamlines the stamping verification process but also realizes a new interaction model to improve the user experience.

[0125] For example, if the emotion engine detects disappointment when a user reviews a stamped document, the server displays a detailed error explanation and support contact information on the screen. This allows the user to intuitively understand what action to take next. In this way, the system provides advanced accessibility and usability, enabling customized services tailored to individual users.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The user scans the application form submitted by the company as digital data and uploads the data to the server. This allows the application form to be incorporated into the system.

[0129] Step 2:

[0130] The server analyzes the received application form data, automatically detects the stamped area using an image processing device, and extracts the image data by cropping the corresponding portion.

[0131] Step 3:

[0132] The server sends the extracted image data of the seal impression to an AI model that analyzes the type of seal impression (round seal, square seal, etc.) and the text information within the impression, and converts it into text data.

[0133] Step 4:

[0134] The acquired text data is organized by company on the server and recorded in a database. This data is used as reference data in the subsequent seal verification process.

[0135] Step 5:

[0136] When a new application form is submitted, the server repeats the same process, comparing the stored text data with the new data. This determines whether the seal is genuine.

[0137] Step 6:

[0138] As soon as a judgment is made regarding the legitimacy of the seal impression, the terminal activates an emotion engine to analyze the user's face and voice in real time and recognize the user's emotional state.

[0139] Step 7:

[0140] Based on the analysis results of the emotion engine, the server generates feedback tailored to the user's emotions and displays it on the device. This feedback can include, for example, gentle voice guidance to alleviate tension or help information when more detailed explanations are needed.

[0141] Step 8:

[0142] The device notifies the user of the final feedback and, if necessary, informs them that visual inspection is not required. This process improves the user experience and increases operational efficiency.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] The present invention aims to solve the problem of improving the user experience by streamlining the process of verifying seals included in application documents and providing feedback that takes user emotions into consideration. Specifically, it aims to reduce the psychological burden on users when receiving feedback on the results in a system that automatically determines the authenticity of seals.

[0146] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0147] In this invention, the server includes means for analyzing the seal impression contained in the application document with an image processing device to identify the type of seal impression and convert the marks within the seal impression into data; means for recording the data in an information recording device that stores data for each organization; means for comparing the seal impression of a newly submitted application document with the stored data in the information recording device and automatically determining whether the seal impression is appropriate according to predetermined criteria; means for analyzing the user's emotions when presenting the judgment result using an emotion recognition device that acquires the user's emotions; and means for providing feedback to a display device that corresponds to the user's state based on the analysis results. This improves the accuracy and efficiency of seal impression verification and makes it possible to create an environment in which users can accept the results with peace of mind.

[0148] An "application document" refers to a formal document created and submitted for various procedures or transactions.

[0149] "Seal impression" refers to the shape or mark left on paper or electronic documents by an imprinted seal or stamp.

[0150] An "image processing device" refers to hardware or software used to analyze, convert, and process information on digital images.

[0151] An "information recording device" refers to a computer system or database used for long-term data storage.

[0152] An "emotion recognition device" refers to a system that possesses technology to analyze a person's facial expressions and voice to estimate their emotional state.

[0153] A "display device" refers to a screen or monitor used to visually display information from a computer or other electronic device.

[0154] "Automated discrimination" refers to the process by which machines or software analyze data and information and make decisions without human intervention.

[0155] In this embodiment of the invention, the analysis of seals included in application documents and the provision of feedback that takes into account the user's emotions are automated.

[0156] Users scan application documents digitally and upload them to the server. The server uses an image processing device to analyze the received data. This device uses libraries such as OpenCV and TENSORFLOW® to analyze and identify the shape of seals and marks. The processed data is registered in an information recording device for each organization and stored for future comparison.

[0157] Next, the server compares the newly submitted seal impression with an existing database. This comparison process utilizes machine learning models, such as TensorFlow, to perform highly accurate analysis. Once the determination is complete, the terminal displays the results to the user.

[0158] The device analyzes the user's facial expressions via an emotion recognition device, using the camera and voice input. This analysis estimates the user's emotional state, and to provide feedback tailored to the user's emotions, relaxing messages and necessary support information are displayed on the screen. This feedback aims to reduce the user's psychological burden.

[0159] As a concrete example, if the emotion recognition device detects disappointment when the user checks the stamping result, the server can display a detailed error explanation and contact information on the terminal. This helps the user intuitively understand what action to take next. An example of a prompt using a generative AI model is, "Please check the stamping on the application form and display feedback on the screen that corresponds to the user's emotion." This enables an efficient and intuitive user experience.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] The user scans the application document digitally and uploads it to the server. The input is the scanned image file, and the output is the data format stored on the server. This procedure converts the physical document into digital data, ready for subsequent processing.

[0163] Step 2:

[0164] The server receives the uploaded image data and uses an image processing device to identify the seal impression. The input is scanned image data, and the output is data with the seal impression extracted. Here, the OpenCV library is used to perform edge detection and contour extraction to determine the location of the seal impression within the image.

[0165] Step 3:

[0166] The server analyzes the detected seal impression data, identifies characters and shapes, and converts them into text data. The input is image data of the seal impression, and the output is text data. Using OCR technology, it reads the character information within the image and stores the data in an information recording device for each organization.

[0167] Step 4:

[0168] The server compares newly submitted seal impression data with existing database data. Input is the old and new seal impression text data, and output is a matching score and classification result. Machine learning libraries such as TensorFlow are used to perform automatic classification according to defined criteria.

[0169] Step 5:

[0170] The device uses an emotion recognition device to analyze the user's emotions in order to present the discrimination results to the user. The input is the user's facial expressions and voice, and the output is the estimated emotional state. During this process, the camera and microphone are used to collect real-time input, and the AI ​​model infers the emotions.

[0171] Step 6:

[0172] The device displays feedback tailored to the user's state based on the results of emotion recognition. Input is the emotional state and the recognition result, while output is appropriate feedback messages and on-screen instructions. It provides reassuring messages, relaxing interfaces, or support information, taking actions to reduce the user's psychological burden.

[0173] (Application Example 2)

[0174] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0175] Traditionally, the process of verifying signatures on application forms has often been performed manually, which is not only prone to misrecognition and time-consuming, but also lacks feedback that takes user emotions into consideration. This can potentially detract from the user experience. The present invention aims to improve the user experience by automating the signature verification process and optimizing feedback by analyzing user emotions.

[0176] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0177] In this invention, the server includes means for analyzing the seal impression contained in the application form with an image processing device to identify the type of seal impression and convert the characters in the seal impression into digital data; means for recording the digital data in a database that stores data for each organization; means for comparing the seal impression of a newly submitted application form with the stored information in the database and determining whether the seal impression is appropriate according to predetermined standards; means for displaying the determination result on a display device; means for analyzing the user's emotional state using an emotion engine and providing an interface based on the analysis result; and means for automatically adjusting the interface according to the customer's emotions and providing elements that promote relaxation. As a result, the process of confirming the seal impression is automated, and flexible feedback according to the user's emotions is possible, improving the user experience.

[0178] An "application form" is a document that a user fills out and submits when entering into a contract for purchasing goods or using a service.

[0179] "Seal impression" refers to image data that includes the shape of a stamped seal and the text information contained within it.

[0180] An "image processing device" is a device that has a computing mechanism for analyzing digital images and extracting various features.

[0181] "Digital data" refers to data obtained by converting analog information into a digital format.

[0182] A "database" is a collection of information that is systematically stored and made retrieval and utilization efficient.

[0183] A "standard" is a benchmark or criterion that serves as a reference for making judgments or evaluations.

[0184] An "emotion engine" is software or a system equipped with an algorithm for analyzing and determining a user's emotions.

[0185] A "display device" is a device that visually displays information output from a computer on a screen.

[0186] An "interface" is a point of contact or means that enables communication between a user and a computer system.

[0187] "Elements that promote relaxation" refer to various means and techniques designed to alleviate the user's tension and anxiety and guide their mind and body into a relaxed state.

[0188] This invention comprises a system that automates the verification of seals on application forms and provides feedback that takes into account the user's emotions. A specific embodiment is shown below.

[0189] First, the user uses a terminal installed in the store to scan the application form required for purchase or contract. The terminal is equipped with a high-precision scanning function to accurately capture the seal impression on the application form. Image processing using OpenCV is performed on this terminal, and the type of seal impression and the text information inside are converted into digital data.

[0190] Next, the converted digital data is uploaded to a server. The server runs a Django-based backend system, and the data is stored in a database operated by each organization. Simultaneously, past seal impression data and new seal impression data are compared within the database, and the system automatically determines whether the seal impression is appropriate according to the regulations. This determination result is immediately displayed on the terminal's screen.

[0191] Furthermore, the server incorporates an emotion engine that analyzes customer facial expressions. The user's facial image, captured by the device's camera, is analyzed in real time using Microsoft® Azure® Face API or Google® Cloud Vision AI. If the user is feeling tense or anxious, the interface automatically adjusts, displaying elements that promote relaxation. These relaxation elements include soft color backgrounds and the playback of calming music.

[0192] For example, when a user checks the results of signing an application form, if the emotion engine detects a stress response from the user's face, the system will gently display intuitive operation guides and take actions to reduce stress. This allows the user to clearly understand what action to take next.

[0193] An example of a prompt when using a generative AI model is, "Analyze customer facial expression data in real time and create an interface that reduces tension."

[0194] Thus, the present invention significantly improves the efficiency of the stamping verification process, enables flexible feedback that responds to customer emotions, and supports the provision of a better user experience.

[0195] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0196] Step 1:

[0197] The user uses a terminal installed in the store to scan the application form. The terminal is equipped with a camera for image processing, which captures the seal impression on the application form. The input is a paper application form, and the output is digital image data.

[0198] Step 2:

[0199] The terminal uses OpenCV to process captured image data, detecting and cropping the position of the seal impression. Here, the shape of the seal impression and internal text information are extracted from the image data and converted into digital data. The input is a scanned image, and the output is digital data that retains the characteristics of the seal impression.

[0200] Step 3:

[0201] The terminal uploads the converted digital data to the server. The server processes the received data using a Django-based platform and stores it in a database structured by organization. The input here is the seal impression data, and the output is the information recorded in the database.

[0202] Step 4:

[0203] The server compares newly uploaded data with existing seal impression data in the database. This process executes a data comparison algorithm based on established procedures. The input consists of the new seal impression data and the stored data in the database, while the output is the judgment result regarding the appropriateness of the seal impression.

[0204] Step 5:

[0205] The terminal receives the decision result from the server and displays it on the screen. In this case, the output indicates whether the decision was appropriate or not, and this is visually fed back to the user.

[0206] Step 6:

[0207] The device captures the user's facial expressions with its camera, and the server analyzes this data using an emotion engine. APIs used include Microsoft Azure Face API and Google Cloud Vision AI. The input is a user's facial image, and the output is their emotional state.

[0208] Step 7:

[0209] The server, based on the analyzed emotional state, prepares and sends a relaxation-promoting interface to the terminal. The input is the user's emotional state, and the output is the generated display interface (changes in color scheme and music). The user interface is dynamically adjusted based on the actions taken.

[0210] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0211] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0212] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0213] [Second Embodiment]

[0214] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0215] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0216] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0217] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0218] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0219] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0220] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0221] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0222] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0223] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0224] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0225] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0226] This invention is a system designed to streamline the process of stamping application forms by specific industries and companies. The system automatically identifies the type and content of the stamp through image analysis of the stamp impression, reducing the need for manual visual verification.

[0227] First, the user scans the application form submitted by the company as digital data and uploads it to the server. This allows the application form data to be imported into the system. The server processes the received application form data and uses an image processing device to extract the stamped portion.

[0228] Once a stamped image is extracted, the server sends it to a generating AI model for detailed analysis. The generating AI model converts the shape and type of the stamp (round, square, etc.) and the characters within the stamp into text data. This text information obtained through analysis is stored in a database as important elements.

[0229] Subsequently, when a new application form is submitted, the server analyzes the application form again and processes the image of the seal impression using an AI model that generates images. The extracted text information is compared with the previously stored data. The server automatically determines the appropriateness of the seal impression based on predetermined criteria and makes a decision based on that result.

[0230] Ultimately, the terminal presents the user with the result of its decision. For example, if the stamp has already been verified, a notification will appear stating that visual inspection is unnecessary. This allows the user to proceed with the verification process quickly and efficiently. This system is expected to automate the stamp verification process and enable the effective use of human resources.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] Users scan application forms submitted by companies and upload the corresponding digital data to the server. This allows the application form data to be imported into the system.

[0234] Step 2:

[0235] The server processes the received application form data, uses an image processing device to detect the stamped area, and performs cropping. This cropping extracts the image data of the stamp.

[0236] Step 3:

[0237] The server sends the extracted stamped image to the generating AI model and requests analysis. The generating AI model analyzes the shape and type of the stamp, as well as the text information within the stamp impression, and returns it as text data.

[0238] Step 4:

[0239] The server organizes the text data obtained from the generated AI models by company and stores it in a database. This database is then made available for reference during subsequent signature checks.

[0240] Step 5:

[0241] When a new application form is submitted, the server receives the application form again, processes the stamped area as an image, and obtains the text data using a generative AI model.

[0242] Step 6:

[0243] The server compares the stored stamp data in the database with the newly acquired data and determines the legitimacy of the stamp according to the specified rules.

[0244] Step 7:

[0245] The terminal displays the results of the stamping check obtained from the server to the user. If there are no problems with the stamping, the user is notified that visual inspection is not required.

[0246] (Example 1)

[0247] Next, we will describe Example 1. 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."

[0248] Traditionally, verifying the authenticity of seals on application forms and other documents has been a time-consuming and labor-intensive process due to the reliance on manual labor. Furthermore, the possibility of human error in the verification process cannot be ruled out. Therefore, there is a need to quickly and automatically determine the appropriateness of seals to improve efficiency and accuracy.

[0249] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0250] In this invention, the server includes means for analyzing the seal impression contained in the application form using an image processing device to identify the shape and type of the seal impression and convert the contents of the seal impression into text data; means for recording the text data in a storage device that stores the data for each organization; and means for analyzing the extracted text data using an artificial intelligence model that generates data and storing the generated information. This makes it possible to automate the process of verifying the seal impression and to make decisions efficiently and accurately.

[0251] An "application form" is an official document submitted to apply for a specific procedure or service.

[0252] An "impression" is the trace of shape or characters left behind when a stamp or seal is pressed onto something.

[0253] An "image processing device" is a system of hardware or software for analyzing, converting, and displaying digital images.

[0254] "Text data" refers to data that represents character information in a digital format.

[0255] An "organization" is a group or institution formed for a specific purpose or activity.

[0256] A "storage device" is hardware or software used to store digital data.

[0257] A "generative artificial intelligence model" is a collection of algorithms built using machine learning and deep learning techniques to analyze, judge, and generate data as input.

[0258] A "display device" is hardware used to present information visually, and usually refers to a screen or monitor.

[0259] This invention is a system for streamlining the process of verifying seals on application forms. Specifically, it is operated through the roles of server, terminal, and user.

[0260] The user first digitizes the application form using a scanner. At this stage, a standard scanning device is used to convert the application form into a PDF or image file (JPEG, PNG, etc.). Next, the user uploads the digitized file to the server. This allows the application data to be imported into the system.

[0261] After receiving the uploaded data, the server analyzes the seal impression portion of the image using an image processing library (e.g., OpenCV). This image processing device recognizes the shape and type of the seal impression and converts the character codes within the impression into digital text data. The converted text data is then stored in a memory device by the server. This stored data plays an important role as it will be used for later comparisons and other purposes.

[0262] Next, the server utilizes a generative AI model to perform a detailed analysis of the extracted text data. The generative AI model uses a deep learning algorithm to analyze the seal impressions and uses the accumulated information to generate new patterns and determine their appropriateness.

[0263] This system significantly automates the stamp verification process. If the stamp is valid, the terminal displays the result to the user, notifying them that further visual verification is unnecessary. This allows users to expedite the verification process and improve overall operational efficiency.

[0264] As a concrete example, consider the application forms used when opening an account at a financial institution such as a bank. By applying this system, it becomes possible to efficiently review the enormous number of application forms on a daily basis.

[0265] Examples of prompt statements are as follows:

[0266] "Please analyze the following stamp image and convert the type of stamp and its contents into text."

[0267] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0268] Step 1:

[0269] The user scans and digitizes the application form. The input is a paper application form, which is converted to a PDF or image file using a scanner. The output is the digitized application form data. This data will be used in the next processing step, so the file format should be standard.

[0270] Step 2:

[0271] Users upload digitized application forms to the server via a dedicated platform. The input is a digital file stored on the user's device. The output is the application form data sent to the server and incorporated into the system. The upload operation is performed using the user interface, and the server accurately receives the file.

[0272] Step 3:

[0273] The server processes the received data using an image processing device. The input is the uploaded application form data (in image or PDF format). An image processing library (e.g., OpenCV) is used to identify and extract the stamped area. The output is the extracted stamped image. This image is used in the next analysis step.

[0274] Step 4:

[0275] The server sends the extracted stamp image to the generation AI model for analysis. The input is image data of the stamp. The generation AI model uses deep learning technology to analyze the shape of the stamp and the content of the characters inside, and generates text data. The output is the analyzed text information. This information is stored in a database for verification.

[0276] Step 5:

[0277] The server compares the generated text data with an existing database. The input consists of newly generated text information and historical records within the database. This allows for data analysis to determine the degree of consistency and appropriateness of the seal impressions. The output is the judgment result regarding the appropriateness of the seal impressions.

[0278] Step 6:

[0279] The terminal displays the results from the server to the user. The input is the decision result sent from the server. The results are visually displayed on the terminal, prompting the user to take the necessary action. The output is a result message presented to the user, which includes information such as "Seal has been confirmed." The user then decides on their next action based on this.

[0280] (Application Example 1)

[0281] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0282] In daily operations, verifying the presence of a seal on a document is a time-consuming and laborious process. This invention aims to efficiently identify the seal impressions on coupons and membership cards in physical stores, reduce the time required for seal verification, and prevent fraudulent use.

[0283] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0284] In this invention, the server includes means for analyzing a visible impression included in an application form with an image processing device to identify the type of the impression and convert symbols in the impression into character data, means for recording the character data in an information storage device that stores the data for each organization, and means for comparing the impression of a newly submitted application form with the stored information in the information storage device and determining whether the seal is appropriate according to a predetermined criterion. Thereby, it becomes possible to automatically recognize and confirm coupons and membership cards in physical stores.

[0285] A "visible impression" is an impression printed in a visible form on paper or a digital screen.

[0286] An "image processing device" is an electronic device for analyzing photographed image data and performing conversion and identification.

[0287] A "symbol" is an identifiable character element such as an alphabet or a number included in an impression.

[0288] "Character data" is information representing the analyzed symbols in digital form. [[ID=]18]

[0289] An "information storage device" is a storage system for storing digital data safely for a long time.

[0290] "Storing for each organization" is a method of individually recording and storing data associated with different groups or corporations.

[0291] "Automatic recognition" is the ability of a machine or software to identify specific patterns or information without human intervention.

[0292] "Means for determining" is a method or process for evaluating whether it is appropriate using a specific criterion based on the input information. [[ID=]33]

[0293] This invention is a system for the automatic recognition and verification of coupons and membership cards within a store. The user uses a smart device to capture a visible imprint of the presented coupon. The captured image data is transmitted to a server in real time.

[0294] The server uses an image processing device to extract visible seal impressions from received images and analyzes the symbols contained within those impressions. A generative AI model is used for this analysis, automatically identifying the type of seal impression and converting the symbols into character data. The converted character data is recorded in information storage devices for each relevant organization.

[0295] Next, the server compares the text data of the newly submitted coupon with information already stored in the information storage device. This comparison determines whether the coupon is valid according to predetermined criteria. The result is immediately output to the terminal's display device and notified to the user. For example, if the coupon is valid, it will display "20% off applied."

[0296] As a concrete example, the generating AI model recognizes and processes a seal impression based on a prompt message such as, "Analyze the seal impression in this image, extract text information, and determine its validity." Based on this prompt message, the AI ​​performs an appropriate analysis, enabling the entire system to operate efficiently.

[0297] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0298] Step 1:

[0299] The user uses a smart device to capture a visible imprint on the presented coupon. This captured image becomes the input. The captured image data is then sent directly to the server.

[0300] Step 2:

[0301] The server analyzes the received image data using an image processing device. Here, data processing is performed to extract visible imprints from the image. The extracted imprints are output and the process proceeds to the next step.

[0302] Step 3:

[0303] The server utilizes a generated AI model to analyze the extracted imprints. The input is the extracted imprints, and data operations are performed to recognize symbols contained within the imprints and convert them into character data. This character data is output and sent to an information storage device.

[0304] Step 4:

[0305] The server records the character data in an information storage device and accumulates it in the database of related organizations as necessary. The input is the converted character data, which is output as the recorded data.

[0306] Step 5:

[0307] A process is performed to compare the character data of the newly submitted coupon with the existing data. The server uses a predetermined criterion to judge the input data and conducts data operations to evaluate the validity of the coupon. The result of the validity judgment is output.

[0308] Step 6:

[0309] The server sends the judgment result to the display device of the terminal. The input here is the result of the validity judgment, and the output to be notified to the user is the display screen. As a specific operation, when the validity is confirmed, the application of discounts, etc. is explicitly shown.

[0310] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0311] This invention is a system that automates the verification of seals on application forms and provides feedback that takes user emotions into consideration. This system operates by combining image processing technology that identifies the type and characters of the seals with an emotion engine that recognizes user emotions.

[0312] First, the user digitally scans the application form submitted by the company and uploads it to the server. The server receives this data and uses an image processing device to detect and analyze the seal portion of the application form. Here, the shape of the seal and the text information within the seal impression are extracted and stored in a database as text data.

[0313] Next, newly submitted application forms are processed in the same manner and compared with accumulated data to automatically evaluate whether the seal impression conforms to the regulations. The emotion engine analyzes the user's facial expressions and voice when the user checks the results to determine their emotional state. As a result, for example, if the user is tense, the device uses relaxing interfaces and notifications to reduce stress.

[0314] Furthermore, convenience is enhanced by providing quick and simple feedback to users who are fully satisfied. This system not only streamlines the stamping verification process but also realizes a new interaction model to improve the user experience.

[0315] For example, if the emotion engine detects disappointment when a user reviews a stamped document, the server displays a detailed error explanation and support contact information on the screen. This allows the user to intuitively understand what action to take next. In this way, the system provides advanced accessibility and usability, enabling customized services tailored to individual users.

[0316] The following describes the processing flow.

[0317] Step 1:

[0318] The user scans the application form submitted by the company as digital data and uploads the data to the server. This allows the application form to be incorporated into the system.

[0319] Step 2:

[0320] The server analyzes the received application form data, automatically detects the stamped area using an image processing device, and extracts the image data by cropping the corresponding portion.

[0321] Step 3:

[0322] The server sends the extracted image data of the seal impression to an AI model that analyzes the type of seal impression (round seal, square seal, etc.) and the text information within the impression, and converts it into text data.

[0323] Step 4:

[0324] The acquired text data is organized by company on the server and recorded in a database. This data is used as reference data in the subsequent seal verification process.

[0325] Step 5:

[0326] When a new application form is submitted, the server repeats the same process, comparing the stored text data with the new data. This determines whether the seal is genuine.

[0327] Step 6:

[0328] As soon as a judgment is made regarding the legitimacy of the seal impression, the terminal activates an emotion engine to analyze the user's face and voice in real time and recognize the user's emotional state.

[0329] Step 7:

[0330] Based on the analysis results of the emotion engine, the server generates feedback tailored to the user's emotions and displays it on the device. This feedback can include, for example, gentle voice guidance to alleviate tension or help information when more detailed explanations are needed.

[0331] Step 8:

[0332] The device notifies the user of the final feedback and, if necessary, informs them that visual inspection is not required. This process improves the user experience and increases operational efficiency.

[0333] (Example 2)

[0334] Next, we will describe Example 2. 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".

[0335] The present invention aims to solve the problem of improving the user experience by streamlining the process of verifying seals included in application documents and providing feedback that takes user emotions into consideration. Specifically, it aims to reduce the psychological burden on users when receiving feedback on the results in a system that automatically determines the authenticity of seals.

[0336] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0337] In this invention, the server includes means for analyzing the seal impression contained in the application document with an image processing device to identify the type of seal impression and convert the marks within the seal impression into data; means for recording the data in an information recording device that stores data for each organization; means for comparing the seal impression of a newly submitted application document with the stored data in the information recording device and automatically determining whether the seal impression is appropriate according to predetermined criteria; means for analyzing the user's emotions when presenting the judgment result using an emotion recognition device that acquires the user's emotions; and means for providing feedback to a display device that corresponds to the user's state based on the analysis results. This improves the accuracy and efficiency of seal impression verification and makes it possible to create an environment in which users can accept the results with peace of mind.

[0338] An "application document" refers to a formal document created and submitted for various procedures or transactions.

[0339] "Seal impression" refers to the shape or mark left on paper or electronic documents by an imprinted seal or stamp.

[0340] An "image processing device" refers to hardware or software used to analyze, convert, and process information on digital images.

[0341] An "information recording device" refers to a computer system or database used for long-term data storage.

[0342] An "emotion recognition device" refers to a system that possesses technology to analyze a person's facial expressions and voice to estimate their emotional state.

[0343] A "display device" refers to a screen or monitor used to visually display information from a computer or other electronic device.

[0344] "Automated discrimination" refers to the process by which machines or software analyze data and information and make decisions without human intervention.

[0345] In this embodiment of the invention, the analysis of seals included in application documents and the provision of feedback that takes into account the user's emotions are automated.

[0346] Users scan application documents digitally and upload them to the server. The server uses an image processing device to analyze the received data. This device uses libraries such as OpenCV and TensorFlow to analyze and identify the shape of seals and marks. The processed data is registered in an information recording device for each organization and stored for future comparison.

[0347] Next, the server compares the newly submitted seal impression with an existing database. This comparison process utilizes machine learning models, such as TensorFlow, to perform highly accurate analysis. Once the determination is complete, the terminal displays the results to the user.

[0348] The device analyzes the user's facial expressions via an emotion recognition device, using the camera and voice input. This analysis estimates the user's emotional state, and to provide feedback tailored to the user's emotions, relaxing messages and necessary support information are displayed on the screen. This feedback aims to reduce the user's psychological burden.

[0349] As a concrete example, if the emotion recognition device detects disappointment when the user checks the stamping result, the server can display a detailed error explanation and contact information on the terminal. This helps the user intuitively understand what action to take next. An example of a prompt using a generative AI model is, "Please check the stamping on the application form and display feedback on the screen that corresponds to the user's emotion." This enables an efficient and intuitive user experience.

[0350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0351] Step 1:

[0352] The user scans the application document digitally and uploads it to the server. The input is the scanned image file, and the output is the data format stored on the server. This procedure converts the physical document into digital data, ready for subsequent processing.

[0353] Step 2:

[0354] The server receives the uploaded image data and uses an image processing device to identify the seal impression. The input is scanned image data, and the output is data with the seal impression extracted. Here, the OpenCV library is used to perform edge detection and contour extraction to determine the location of the seal impression within the image.

[0355] Step 3:

[0356] The server analyzes the detected seal impression data, identifies characters and shapes, and converts them into text data. The input is image data of the seal impression, and the output is text data. Using OCR technology, it reads the character information within the image and stores the data in an information recording device for each organization.

[0357] Step 4:

[0358] The server compares newly submitted seal impression data with existing database data. Input is the old and new seal impression text data, and output is a matching score and classification result. Machine learning libraries such as TensorFlow are used to perform automatic classification according to defined criteria.

[0359] Step 5:

[0360] The device uses an emotion recognition device to analyze the user's emotions in order to present the discrimination results to the user. The input is the user's facial expressions and voice, and the output is the estimated emotional state. During this process, the camera and microphone are used to collect real-time input, and the AI ​​model infers the emotions.

[0361] Step 6:

[0362] The device displays feedback tailored to the user's state based on the results of emotion recognition. Input is the emotional state and the recognition result, while output is appropriate feedback messages and on-screen instructions. It provides reassuring messages, relaxing interfaces, or support information, taking actions to reduce the user's psychological burden.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0365] Traditionally, the process of verifying signatures on application forms has often been performed manually, which is not only prone to misrecognition and time-consuming, but also lacks feedback that takes user emotions into consideration. This can potentially detract from the user experience. The present invention aims to improve the user experience by automating the signature verification process and optimizing feedback by analyzing user emotions.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes means for analyzing the seal impression contained in the application form with an image processing device to identify the type of seal impression and convert the characters in the seal impression into digital data; means for recording the digital data in a database that stores data for each organization; means for comparing the seal impression of a newly submitted application form with the stored information in the database and determining whether the seal impression is appropriate according to predetermined standards; means for displaying the determination result on a display device; means for analyzing the user's emotional state using an emotion engine and providing an interface based on the analysis result; and means for automatically adjusting the interface according to the customer's emotions and providing elements that promote relaxation. As a result, the process of confirming the seal impression is automated, and flexible feedback according to the user's emotions is possible, improving the user experience.

[0368] An "application form" is a document that a user fills out and submits when entering into a contract for purchasing goods or using a service.

[0369] "Seal impression" refers to image data that includes the shape of a stamped seal and the text information contained within it.

[0370] An "image processing device" is a device that has a computing mechanism for analyzing digital images and extracting various features.

[0371] "Digital data" refers to data obtained by converting analog information into a digital format.

[0372] A "database" is a collection of information that is systematically stored and made retrieval and utilization efficient.

[0373] A "standard" is a benchmark or criterion that serves as a reference for making judgments or evaluations.

[0374] An "emotion engine" is software or a system equipped with an algorithm for analyzing and determining a user's emotions.

[0375] A "display device" is a device that visually displays information output from a computer on a screen.

[0376] An "interface" is a point of contact or means that enables communication between a user and a computer system.

[0377] "Elements that promote relaxation" refer to various means and techniques designed to alleviate the user's tension and anxiety and guide their mind and body into a relaxed state.

[0378] This invention comprises a system that automates the verification of seals on application forms and provides feedback that takes into account the user's emotions. A specific embodiment is shown below.

[0379] First, the user uses a terminal installed in the store to scan the application form required for purchase or contract. The terminal is equipped with a high-precision scanning function to accurately capture the seal impression on the application form. Image processing using OpenCV is performed on this terminal, and the type of seal impression and the text information inside are converted into digital data.

[0380] Next, the converted digital data is uploaded to a server. The server runs a Django-based backend system, and the data is stored in a database operated by each organization. Simultaneously, past seal impression data and new seal impression data are compared within the database, and the system automatically determines whether the seal impression is appropriate according to the regulations. This determination result is immediately displayed on the terminal's screen.

[0381] Furthermore, the server incorporates an emotion engine that analyzes customer facial expressions. The user's facial image, captured by the device's camera, undergoes real-time emotion analysis using the Microsoft Azure Face API or Google Cloud Vision AI. If the user is feeling tense or anxious, the interface automatically adjusts, displaying elements that promote relaxation. These relaxation elements include soft color backgrounds and the playback of calming music.

[0382] For example, when a user checks the results of signing an application form, if the emotion engine detects a stress response from the user's face, the system will gently display intuitive operation guides and take actions to reduce stress. This allows the user to clearly understand what action to take next.

[0383] An example of a prompt when using a generative AI model is, "Analyze customer facial expression data in real time and create an interface that reduces tension."

[0384] Thus, the present invention significantly improves the efficiency of the stamping verification process, enables flexible feedback that responds to customer emotions, and supports the provision of a better user experience.

[0385] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0386] Step 1:

[0387] The user uses a terminal installed in the store to scan the application form. The terminal is equipped with a camera for image processing, which captures the seal impression on the application form. The input is a paper application form, and the output is digital image data.

[0388] Step 2:

[0389] The terminal uses OpenCV to process captured image data, detecting and cropping the position of the seal impression. Here, the shape of the seal impression and internal text information are extracted from the image data and converted into digital data. The input is a scanned image, and the output is digital data that retains the characteristics of the seal impression.

[0390] Step 3:

[0391] The terminal uploads the converted digital data to the server. The server processes the received data using a Django-based platform and stores it in a database structured by organization. The input here is the seal impression data, and the output is the information recorded in the database.

[0392] Step 4:

[0393] The server compares newly uploaded data with existing seal impression data in the database. This process executes a data comparison algorithm based on established procedures. The input consists of the new seal impression data and the stored data in the database, while the output is the judgment result regarding the appropriateness of the seal impression.

[0394] Step 5:

[0395] The terminal receives the decision result from the server and displays it on the screen. In this case, the output indicates whether the decision was appropriate or not, and this is visually fed back to the user.

[0396] Step 6:

[0397] The device captures the user's facial expressions with its camera, and the server analyzes this data using an emotion engine. APIs used include Microsoft Azure Face API and Google Cloud Vision AI. The input is a user's facial image, and the output is their emotional state.

[0398] Step 7:

[0399] The server, based on the analyzed emotional state, prepares and sends a relaxation-promoting interface to the terminal. The input is the user's emotional state, and the output is the generated display interface (changes in color scheme and music). The user interface is dynamically adjusted based on the actions taken.

[0400] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0401] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0402] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0403] [Third Embodiment]

[0404] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0405] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0406] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0407] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0408] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0409] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0410] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0411] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0412] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0413] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0414] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0415] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0416] This invention is a system designed to streamline the process of stamping application forms by specific industries and companies. The system automatically identifies the type and content of the stamp through image analysis of the stamp impression, reducing the need for manual visual verification.

[0417] First, the user scans the application form submitted by the company as digital data and uploads it to the server. This allows the application form data to be imported into the system. The server processes the received application form data and uses an image processing device to extract the stamped portion.

[0418] Once a stamped image is extracted, the server sends it to a generating AI model for detailed analysis. The generating AI model converts the shape and type of the stamp (round, square, etc.) and the characters within the stamp into text data. This text information obtained through analysis is stored in a database as important elements.

[0419] Subsequently, when a new application form is submitted, the server analyzes the application form again and processes the image of the seal impression using an AI model that generates images. The extracted text information is compared with the previously stored data. The server automatically determines the appropriateness of the seal impression based on predetermined criteria and makes a decision based on that result.

[0420] Ultimately, the terminal presents the user with the result of its decision. For example, if the stamp has already been verified, a notification will appear stating that visual inspection is unnecessary. This allows the user to proceed with the verification process quickly and efficiently. This system is expected to automate the stamp verification process and enable the effective use of human resources.

[0421] The following describes the processing flow.

[0422] Step 1:

[0423] Users scan application forms submitted by companies and upload the corresponding digital data to the server. This allows the application form data to be imported into the system.

[0424] Step 2:

[0425] The server processes the received application form data, uses an image processing device to detect the stamped area, and performs cropping. This cropping extracts the image data of the stamp.

[0426] Step 3:

[0427] The server sends the extracted stamped image to the generating AI model and requests analysis. The generating AI model analyzes the shape and type of the stamp, as well as the text information within the stamp impression, and returns it as text data.

[0428] Step 4:

[0429] The server organizes the text data obtained from the generated AI models by company and stores it in a database. This database is then made available for reference during subsequent signature checks.

[0430] Step 5:

[0431] When a new application form is submitted, the server receives the application form again, processes the stamped area as an image, and obtains the text data using a generative AI model.

[0432] Step 6:

[0433] The server compares the stored stamp data in the database with the newly acquired data and determines the legitimacy of the stamp according to the specified rules.

[0434] Step 7:

[0435] The terminal displays the results of the stamping check obtained from the server to the user. If there are no problems with the stamping, the user is notified that visual inspection is not required.

[0436] (Example 1)

[0437] Next, we will describe Example 1. 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."

[0438] Traditionally, verifying the authenticity of seals on application forms and other documents has been a time-consuming and labor-intensive process due to the reliance on manual labor. Furthermore, the possibility of human error in the verification process cannot be ruled out. Therefore, there is a need to quickly and automatically determine the appropriateness of seals to improve efficiency and accuracy.

[0439] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0440] In this invention, the server includes means for analyzing the seal impression contained in the application form using an image processing device to identify the shape and type of the seal impression and convert the contents of the seal impression into text data; means for recording the text data in a storage device that stores the data for each organization; and means for analyzing the extracted text data using an artificial intelligence model that generates data and storing the generated information. This makes it possible to automate the process of verifying the seal impression and to make decisions efficiently and accurately.

[0441] An "application form" is an official document submitted to apply for a specific procedure or service.

[0442] An "impression" is the trace of shape or characters left behind when a stamp or seal is pressed onto something.

[0443] An "image processing device" is a system of hardware or software for analyzing, converting, and displaying digital images.

[0444] "Text data" refers to data that represents character information in a digital format.

[0445] An "organization" is a group or institution formed for a specific purpose or activity.

[0446] A "storage device" is hardware or software used to store digital data.

[0447] A "generative artificial intelligence model" is a collection of algorithms built using machine learning and deep learning techniques to analyze, judge, and generate data as input.

[0448] A "display device" is hardware used to present information visually, and usually refers to a screen or monitor.

[0449] This invention is a system for streamlining the process of verifying seals on application forms. Specifically, it is operated through the roles of server, terminal, and user.

[0450] The user first digitizes the application form using a scanner. At this stage, a standard scanning device is used to convert the application form into a PDF or image file (JPEG, PNG, etc.). Next, the user uploads the digitized file to the server. This allows the application data to be imported into the system.

[0451] After receiving the uploaded data, the server analyzes the seal impression portion of the image using an image processing library (e.g., OpenCV). This image processing device recognizes the shape and type of the seal impression and converts the character codes within the impression into digital text data. The converted text data is then stored in a memory device by the server. This stored data plays an important role as it will be used for later comparisons and other purposes.

[0452] Next, the server utilizes a generative AI model to perform a detailed analysis of the extracted text data. The generative AI model uses a deep learning algorithm to analyze the seal impressions and uses the accumulated information to generate new patterns and determine their appropriateness.

[0453] This system significantly automates the stamp verification process. If the stamp is valid, the terminal displays the result to the user, notifying them that further visual verification is unnecessary. This allows users to expedite the verification process and improve overall operational efficiency.

[0454] As a concrete example, consider the application forms used when opening an account at a financial institution such as a bank. By applying this system, it becomes possible to efficiently review the enormous number of application forms on a daily basis.

[0455] Examples of prompt statements are as follows:

[0456] "Please analyze the following stamp image and convert the type of stamp and its contents into text."

[0457] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0458] Step 1:

[0459] The user scans and digitizes the application form. The input is a paper application form, which is converted to a PDF or image file using a scanner. The output is the digitized application form data. This data will be used in the next processing step, so the file format should be standard.

[0460] Step 2:

[0461] Users upload digitized application forms to the server via a dedicated platform. The input is a digital file stored on the user's device. The output is the application form data sent to the server and incorporated into the system. The upload operation is performed using the user interface, and the server accurately receives the file.

[0462] Step 3:

[0463] The server processes the received data using an image processing device. The input is the uploaded application form data (in image or PDF format). An image processing library (e.g., OpenCV) is used to identify and extract the stamped area. The output is the extracted stamped image. This image is used in the next analysis step.

[0464] Step 4:

[0465] The server sends the extracted stamp image to the generation AI model for analysis. The input is image data of the stamp. The generation AI model uses deep learning technology to analyze the shape of the stamp and the content of the characters inside, and generates text data. The output is the analyzed text information. This information is stored in a database for verification.

[0466] Step 5:

[0467] The server compares the generated text data with an existing database. The input consists of newly generated text information and historical records within the database. This allows for data analysis to determine the degree of consistency and appropriateness of the seal impressions. The output is the judgment result regarding the appropriateness of the seal impressions.

[0468] Step 6:

[0469] The terminal displays the results from the server to the user. The input is the decision result sent from the server. The results are visually displayed on the terminal, prompting the user to take the necessary action. The output is a result message presented to the user, which includes information such as "Seal has been confirmed." The user then decides on their next action based on this.

[0470] (Application Example 1)

[0471] Next, we will explain Application Example 1. In the following explanation, 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."

[0472] In daily operations, verifying the presence of a seal on a document is a time-consuming and laborious process. This invention aims to efficiently identify the seal impressions on coupons and membership cards in physical stores, reduce the time required for seal verification, and prevent fraudulent use.

[0473] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0474] In this invention, the server includes means for analyzing the visible seal impression contained in the application form using an image processing device, identifying the type of seal impression, and converting the symbols within the seal impression into character data; means for recording the character data in an information storage device that stores data for each organization; and means for comparing the seal impression of a newly submitted application form with the stored information in the information storage device and determining whether the seal impression is appropriate according to predetermined standards. This enables automatic recognition and verification of coupons and membership cards in physical stores.

[0475] A "visible impression" is an impression that is imprinted in a form that is visible on paper or a digital screen.

[0476] An "image processing device" is an electronic device used to analyze, convert, and identify captured image data.

[0477] A "symbol" refers to an identifiable character element, such as an alphabet or number, included within the seal impression.

[0478] "Character data" refers to information that represents analyzed symbols in digital format.

[0479] An "information storage device" is a storage system for securely storing digital data over long periods of time.

[0480] "Storing data by organization" refers to a method of individually recording and storing data associated with different groups or corporations.

[0481] "Automatic recognition" is the ability of a machine or software to identify specific patterns or information without human intervention.

[0482] "Means of judgment" refers to a method or process of evaluating whether something is appropriate or not using specific criteria based on the information that has been entered.

[0483] This invention is a system for the automatic recognition and verification of coupons and membership cards within a store. The user uses a smart device to capture a visible imprint of the presented coupon. The captured image data is transmitted to a server in real time.

[0484] The server uses an image processing device to extract visible seal impressions from received images and analyzes the symbols contained within those impressions. A generative AI model is used for this analysis, automatically identifying the type of seal impression and converting the symbols into character data. The converted character data is recorded in information storage devices for each relevant organization.

[0485] Next, the server compares the text data of the newly submitted coupon with information already stored in the information storage device. This comparison determines whether the coupon is valid according to predetermined criteria. The result is immediately output to the terminal's display device and notified to the user. For example, if the coupon is valid, it will display "20% off applied."

[0486] As a concrete example, the generating AI model recognizes and processes a seal impression based on a prompt message such as, "Analyze the seal impression in this image, extract text information, and determine its validity." Based on this prompt message, the AI ​​performs an appropriate analysis, enabling the entire system to operate efficiently.

[0487] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0488] Step 1:

[0489] The user uses a smart device to capture a visible imprint on the presented coupon. This captured image becomes the input. The captured image data is then sent directly to the server.

[0490] Step 2:

[0491] The server analyzes the received image data using an image processing device. Here, data processing is performed to extract visible seal impressions from the image. The extracted seal impressions become the output, and the process proceeds to the next stage.

[0492] Step 3:

[0493] The server utilizes a generation AI model to analyze the extracted seal impressions. The input is the extracted seal impressions, and it performs data calculations to recognize the symbols contained within the impressions and convert them into character data. This character data becomes the output and is sent to the information storage device.

[0494] Step 4:

[0495] The server records character data in an information storage device and stores it in the database of the relevant organization as needed. The input is converted character data, and the output is recorded data.

[0496] Step 5:

[0497] The system compares the text data of newly submitted coupons with existing data. The server uses predetermined criteria to evaluate the input data and performs data calculations to assess the validity of the coupons. The results of the validity assessment are then output.

[0498] Step 6:

[0499] The server sends the judgment result to the terminal's display device. The input here is the judgment result of the suitability, and the output notified to the user is the display screen. Specifically, if the validity is confirmed, the application of discounts, etc., will be clearly indicated.

[0500] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0501] This invention is a system that automates the verification of seals on application forms and provides feedback that takes user emotions into consideration. This system operates by combining image processing technology that identifies the type and characters of the seals with an emotion engine that recognizes user emotions.

[0502] First, the user digitally scans the application form submitted by the company and uploads it to the server. The server receives this data and uses an image processing device to detect and analyze the seal portion of the application form. Here, the shape of the seal and the text information within the seal impression are extracted and stored in a database as text data.

[0503] Next, newly submitted application forms are processed in the same manner and compared with accumulated data to automatically evaluate whether the seal impression conforms to the regulations. The emotion engine analyzes the user's facial expressions and voice when the user checks the results to determine their emotional state. As a result, for example, if the user is tense, the device uses relaxing interfaces and notifications to reduce stress.

[0504] Furthermore, convenience is enhanced by providing quick and simple feedback to users who are fully satisfied. This system not only streamlines the stamping verification process but also realizes a new interaction model to improve the user experience.

[0505] For example, if the emotion engine detects disappointment when a user reviews a stamped document, the server displays a detailed error explanation and support contact information on the screen. This allows the user to intuitively understand what action to take next. In this way, the system provides advanced accessibility and usability, enabling customized services tailored to individual users.

[0506] The following describes the processing flow.

[0507] Step 1:

[0508] The user scans the application form submitted by the company as digital data and uploads the data to the server. This allows the application form to be incorporated into the system.

[0509] Step 2:

[0510] The server analyzes the received application form data, automatically detects the stamped area using an image processing device, and extracts the image data by cropping the corresponding portion.

[0511] Step 3:

[0512] The server sends the extracted image data of the seal impression to an AI model that analyzes the type of seal impression (round seal, square seal, etc.) and the text information within the impression, and converts it into text data.

[0513] Step 4:

[0514] The acquired text data is organized by company on the server and recorded in a database. This data is used as reference data in the subsequent seal verification process.

[0515] Step 5:

[0516] When a new application form is submitted, the server repeats the same process, comparing the stored text data with the new data. This determines whether the seal is genuine.

[0517] Step 6:

[0518] As soon as a judgment is made regarding the legitimacy of the seal impression, the terminal activates an emotion engine to analyze the user's face and voice in real time and recognize the user's emotional state.

[0519] Step 7:

[0520] Based on the analysis results of the emotion engine, the server generates feedback tailored to the user's emotions and displays it on the device. This feedback can include, for example, gentle voice guidance to alleviate tension or help information when more detailed explanations are needed.

[0521] Step 8:

[0522] The device notifies the user of the final feedback and, if necessary, informs them that visual inspection is not required. This process improves the user experience and increases operational efficiency.

[0523] (Example 2)

[0524] Next, we will describe Example 2. 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."

[0525] The present invention aims to solve the problem of improving the user experience by streamlining the process of verifying seals included in application documents and providing feedback that takes user emotions into consideration. Specifically, it aims to reduce the psychological burden on users when receiving feedback on the results in a system that automatically determines the authenticity of seals.

[0526] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0527] In this invention, the server includes means for analyzing the seal impression contained in the application document with an image processing device to identify the type of seal impression and convert the marks within the seal impression into data; means for recording the data in an information recording device that stores data for each organization; means for comparing the seal impression of a newly submitted application document with the stored data in the information recording device and automatically determining whether the seal impression is appropriate according to predetermined criteria; means for analyzing the user's emotions when presenting the judgment result using an emotion recognition device that acquires the user's emotions; and means for providing feedback to a display device that corresponds to the user's state based on the analysis results. This improves the accuracy and efficiency of seal impression verification and makes it possible to create an environment in which users can accept the results with peace of mind.

[0528] An "application document" refers to a formal document created and submitted for various procedures or transactions.

[0529] "Seal impression" refers to the shape or mark left on paper or electronic documents by an imprinted seal or stamp.

[0530] An "image processing device" refers to hardware or software used to analyze, convert, and process information on digital images.

[0531] An "information recording device" refers to a computer system or database used for long-term data storage.

[0532] An "emotion recognition device" refers to a system that possesses technology to analyze a person's facial expressions and voice to estimate their emotional state.

[0533] A "display device" refers to a screen or monitor used to visually display information from a computer or other electronic device.

[0534] "Automated discrimination" refers to the process by which machines or software analyze data and information and make decisions without human intervention.

[0535] In this embodiment of the invention, the analysis of seals included in application documents and the provision of feedback that takes into account the user's emotions are automated.

[0536] Users scan application documents digitally and upload them to the server. The server uses an image processing device to analyze the received data. This device uses libraries such as OpenCV and TensorFlow to analyze and identify the shape of seals and marks. The processed data is registered in an information recording device for each organization and stored for future comparison.

[0537] Next, the server compares the newly submitted seal impression with an existing database. This comparison process utilizes machine learning models, such as TensorFlow, to perform highly accurate analysis. Once the determination is complete, the terminal displays the results to the user.

[0538] The device analyzes the user's facial expressions via an emotion recognition device, using the camera and voice input. This analysis estimates the user's emotional state, and to provide feedback tailored to the user's emotions, relaxing messages and necessary support information are displayed on the screen. This feedback aims to reduce the user's psychological burden.

[0539] As a concrete example, if the emotion recognition device detects disappointment when the user checks the stamping result, the server can display a detailed error explanation and contact information on the terminal. This helps the user intuitively understand what action to take next. An example of a prompt using a generative AI model is, "Please check the stamping on the application form and display feedback on the screen that corresponds to the user's emotion." This enables an efficient and intuitive user experience.

[0540] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0541] Step 1:

[0542] The user scans the application document digitally and uploads it to the server. The input is the scanned image file, and the output is the data format stored on the server. This procedure converts the physical document into digital data, ready for subsequent processing.

[0543] Step 2:

[0544] The server receives the uploaded image data and uses an image processing device to identify the seal impression. The input is scanned image data, and the output is data with the seal impression extracted. Here, the OpenCV library is used to perform edge detection and contour extraction to determine the location of the seal impression within the image.

[0545] Step 3:

[0546] The server analyzes the detected seal impression data, identifies characters and shapes, and converts them into text data. The input is image data of the seal impression, and the output is text data. Using OCR technology, it reads the character information within the image and stores the data in an information recording device for each organization.

[0547] Step 4:

[0548] The server compares newly submitted seal impression data with existing database data. Input is the old and new seal impression text data, and output is a matching score and classification result. Machine learning libraries such as TensorFlow are used to perform automatic classification according to defined criteria.

[0549] Step 5:

[0550] The device uses an emotion recognition device to analyze the user's emotions in order to present the discrimination results to the user. The input is the user's facial expressions and voice, and the output is the estimated emotional state. During this process, the camera and microphone are used to collect real-time input, and the AI ​​model infers the emotions.

[0551] Step 6:

[0552] The device displays feedback tailored to the user's state based on the results of emotion recognition. Input is the emotional state and the recognition result, while output is appropriate feedback messages and on-screen instructions. It provides reassuring messages, relaxing interfaces, or support information, taking actions to reduce the user's psychological burden.

[0553] (Application Example 2)

[0554] Next, we will explain application example 2. In the following explanation, 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."

[0555] Traditionally, the process of verifying signatures on application forms has often been performed manually, which is not only prone to misrecognition and time-consuming, but also lacks feedback that takes user emotions into consideration. This can potentially detract from the user experience. The present invention aims to improve the user experience by automating the signature verification process and optimizing feedback by analyzing user emotions.

[0556] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0557] In this invention, the server includes means for analyzing the seal impression contained in the application form with an image processing device to identify the type of seal impression and convert the characters in the seal impression into digital data; means for recording the digital data in a database that stores data for each organization; means for comparing the seal impression of a newly submitted application form with the stored information in the database and determining whether the seal impression is appropriate according to predetermined standards; means for displaying the determination result on a display device; means for analyzing the user's emotional state using an emotion engine and providing an interface based on the analysis result; and means for automatically adjusting the interface according to the customer's emotions and providing elements that promote relaxation. As a result, the process of confirming the seal impression is automated, and flexible feedback according to the user's emotions is possible, improving the user experience.

[0558] An "application form" is a document that a user fills out and submits when entering into a contract for purchasing goods or using a service.

[0559] "Seal impression" refers to image data that includes the shape of a stamped seal and the text information contained within it.

[0560] An "image processing device" is a device that has a computing mechanism for analyzing digital images and extracting various features.

[0561] "Digital data" refers to data obtained by converting analog information into a digital format.

[0562] A "database" is a collection of information that is systematically stored and made retrieval and utilization efficient.

[0563] A "standard" is a benchmark or criterion that serves as a reference for making judgments or evaluations.

[0564] An "emotion engine" is software or a system equipped with an algorithm for analyzing and determining a user's emotions.

[0565] A "display device" is a device that visually displays information output from a computer on a screen.

[0566] An "interface" is a point of contact or means that enables communication between a user and a computer system.

[0567] "Elements that promote relaxation" refer to various means and techniques designed to alleviate the user's tension and anxiety and guide their mind and body into a relaxed state.

[0568] This invention comprises a system that automates the verification of seals on application forms and provides feedback that takes into account the user's emotions. A specific embodiment is shown below.

[0569] First, the user uses a terminal installed in the store to scan the application form required for purchase or contract. The terminal is equipped with a high-precision scanning function to accurately capture the seal impression on the application form. Image processing using OpenCV is performed on this terminal, and the type of seal impression and the text information inside are converted into digital data.

[0570] Next, the converted digital data is uploaded to a server. The server runs a Django-based backend system, and the data is stored in a database operated by each organization. Simultaneously, past seal impression data and new seal impression data are compared within the database, and the system automatically determines whether the seal impression is appropriate according to the regulations. This determination result is immediately displayed on the terminal's screen.

[0571] Furthermore, the server incorporates an emotion engine that analyzes customer facial expressions. The user's facial image, captured by the device's camera, undergoes real-time emotion analysis using the Microsoft Azure Face API or Google Cloud Vision AI. If the user is feeling tense or anxious, the interface automatically adjusts, displaying elements that promote relaxation. These relaxation elements include soft color backgrounds and the playback of calming music.

[0572] For example, when a user checks the results of signing an application form, if the emotion engine detects a stress response from the user's face, the system will gently display intuitive operation guides and take actions to reduce stress. This allows the user to clearly understand what action to take next.

[0573] An example of a prompt when using a generative AI model is, "Analyze customer facial expression data in real time and create an interface that reduces tension."

[0574] Thus, the present invention significantly improves the efficiency of the stamping verification process, enables flexible feedback that responds to customer emotions, and supports the provision of a better user experience.

[0575] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0576] Step 1:

[0577] The user uses a terminal installed in the store to scan the application form. The terminal is equipped with a camera for image processing, which captures the seal impression on the application form. The input is a paper application form, and the output is digital image data.

[0578] Step 2:

[0579] The terminal uses OpenCV to process captured image data, detecting and cropping the position of the seal impression. Here, the shape of the seal impression and internal text information are extracted from the image data and converted into digital data. The input is a scanned image, and the output is digital data that retains the characteristics of the seal impression.

[0580] Step 3:

[0581] The terminal uploads the converted digital data to the server. The server processes the received data using a Django-based platform and stores it in a database structured by organization. The input here is the seal impression data, and the output is the information recorded in the database.

[0582] Step 4:

[0583] The server compares newly uploaded data with existing seal impression data in the database. This process executes a data comparison algorithm based on established procedures. The input consists of the new seal impression data and the stored data in the database, while the output is the judgment result regarding the appropriateness of the seal impression.

[0584] Step 5:

[0585] The terminal receives the decision result from the server and displays it on the screen. In this case, the output indicates whether the decision was appropriate or not, and this is visually fed back to the user.

[0586] Step 6:

[0587] The device captures the user's facial expressions with its camera, and the server analyzes this data using an emotion engine. APIs used include Microsoft Azure Face API and Google Cloud Vision AI. The input is a user's facial image, and the output is their emotional state.

[0588] Step 7:

[0589] The server, based on the analyzed emotional state, prepares and sends a relaxation-promoting interface to the terminal. The input is the user's emotional state, and the output is the generated display interface (changes in color scheme and music). The user interface is dynamically adjusted based on the actions taken.

[0590] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0591] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0592] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0593] [Fourth Embodiment]

[0594] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0595] As shown in Figure 7, the 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.

[0596] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0597] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0598] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0599] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0600] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0601] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0602] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0603] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0604] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0605] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0606] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0607] This invention is a system designed to streamline the process of stamping application forms by specific industries and companies. The system automatically identifies the type and content of the stamp through image analysis of the stamp impression, reducing the need for manual visual verification.

[0608] First, the user scans the application form submitted by the company as digital data and uploads it to the server. This allows the application form data to be imported into the system. The server processes the received application form data and uses an image processing device to extract the stamped portion.

[0609] Once a stamped image is extracted, the server sends it to a generating AI model for detailed analysis. The generating AI model converts the shape and type of the stamp (round, square, etc.) and the characters within the stamp into text data. This text information obtained through analysis is stored in a database as important elements.

[0610] Subsequently, when a new application form is submitted, the server analyzes the application form again and processes the image of the seal impression using an AI model that generates images. The extracted text information is compared with the previously stored data. The server automatically determines the appropriateness of the seal impression based on predetermined criteria and makes a decision based on that result.

[0611] Ultimately, the terminal presents the user with the result of its decision. For example, if the stamp has already been verified, a notification will appear stating that visual inspection is unnecessary. This allows the user to proceed with the verification process quickly and efficiently. This system is expected to automate the stamp verification process and enable the effective use of human resources.

[0612] The following describes the processing flow.

[0613] Step 1:

[0614] Users scan application forms submitted by companies and upload the corresponding digital data to the server. This allows the application form data to be imported into the system.

[0615] Step 2:

[0616] The server processes the received application form data, uses an image processing device to detect the stamped area, and performs cropping. This cropping extracts the image data of the stamp.

[0617] Step 3:

[0618] The server sends the extracted stamped image to the generating AI model and requests analysis. The generating AI model analyzes the shape and type of the stamp, as well as the text information within the stamp impression, and returns it as text data.

[0619] Step 4:

[0620] The server organizes the text data obtained from the generated AI models by company and stores it in a database. This database is then made available for reference during subsequent signature checks.

[0621] Step 5:

[0622] When a new application form is submitted, the server receives the application form again, processes the stamped area as an image, and obtains the text data using a generative AI model.

[0623] Step 6:

[0624] The server compares the stored stamp data in the database with the newly acquired data and determines the legitimacy of the stamp according to the specified rules.

[0625] Step 7:

[0626] The terminal displays the results of the stamping check obtained from the server to the user. If there are no problems with the stamping, the user is notified that visual inspection is not required.

[0627] (Example 1)

[0628] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0629] Traditionally, verifying the authenticity of seals on application forms and other documents has been a time-consuming and labor-intensive process due to the reliance on manual labor. Furthermore, the possibility of human error in the verification process cannot be ruled out. Therefore, there is a need to quickly and automatically determine the appropriateness of seals to improve efficiency and accuracy.

[0630] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0631] In this invention, the server includes means for analyzing the seal impression contained in the application form using an image processing device to identify the shape and type of the seal impression and convert the contents of the seal impression into text data; means for recording the text data in a storage device that stores the data for each organization; and means for analyzing the extracted text data using an artificial intelligence model that generates data and storing the generated information. This makes it possible to automate the process of verifying the seal impression and to make decisions efficiently and accurately.

[0632] An "application form" is an official document submitted to apply for a specific procedure or service.

[0633] An "impression" is the trace of shape or characters left behind when a stamp or seal is pressed onto something.

[0634] An "image processing device" is a system of hardware or software for analyzing, converting, and displaying digital images.

[0635] "Text data" refers to data that represents character information in a digital format.

[0636] An "organization" is a group or institution formed for a specific purpose or activity.

[0637] A "storage device" is hardware or software used to store digital data.

[0638] A "generative artificial intelligence model" is a collection of algorithms built using machine learning and deep learning techniques to analyze, judge, and generate data as input.

[0639] A "display device" is hardware used to present information visually, and usually refers to a screen or monitor.

[0640] This invention is a system for streamlining the process of verifying seals on application forms. Specifically, it is operated through the roles of server, terminal, and user.

[0641] The user first digitizes the application form using a scanner. At this stage, a standard scanning device is used to convert the application form into a PDF or image file (JPEG, PNG, etc.). Next, the user uploads the digitized file to the server. This allows the application data to be imported into the system.

[0642] After receiving the uploaded data, the server analyzes the seal impression portion of the image using an image processing library (e.g., OpenCV). This image processing device recognizes the shape and type of the seal impression and converts the character codes within the impression into digital text data. The converted text data is then stored in a memory device by the server. This stored data plays an important role as it will be used for later comparisons and other purposes.

[0643] Next, the server utilizes a generative AI model to perform a detailed analysis of the extracted text data. The generative AI model uses a deep learning algorithm to analyze the seal impressions and uses the accumulated information to generate new patterns and determine their appropriateness.

[0644] This system significantly automates the stamp verification process. If the stamp is valid, the terminal displays the result to the user, notifying them that further visual verification is unnecessary. This allows users to expedite the verification process and improve overall operational efficiency.

[0645] As a concrete example, consider the application forms used when opening an account at a financial institution such as a bank. By applying this system, it becomes possible to efficiently review the enormous number of application forms on a daily basis.

[0646] Examples of prompt statements are as follows:

[0647] "Please analyze the following stamp image and convert the type of stamp and its contents into text."

[0648] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0649] Step 1:

[0650] The user scans and digitizes the application form. The input is a paper application form, which is converted to a PDF or image file using a scanner. The output is the digitized application form data. This data will be used in the next processing step, so the file format should be standard.

[0651] Step 2:

[0652] Users upload digitized application forms to the server via a dedicated platform. The input is a digital file stored on the user's device. The output is the application form data sent to the server and incorporated into the system. The upload operation is performed using the user interface, and the server accurately receives the file.

[0653] Step 3:

[0654] The server processes the received data using an image processing device. The input is the uploaded application form data (in image or PDF format). An image processing library (e.g., OpenCV) is used to identify and extract the stamped area. The output is the extracted stamped image. This image is used in the next analysis step.

[0655] Step 4:

[0656] The server sends the extracted stamp image to the generation AI model for analysis. The input is image data of the stamp. The generation AI model uses deep learning technology to analyze the shape of the stamp and the content of the characters inside, and generates text data. The output is the analyzed text information. This information is stored in a database for verification.

[0657] Step 5:

[0658] The server compares the generated text data with an existing database. The input consists of newly generated text information and historical records within the database. This allows for data analysis to determine the degree of consistency and appropriateness of the seal impressions. The output is the judgment result regarding the appropriateness of the seal impressions.

[0659] Step 6:

[0660] The terminal displays the results from the server to the user. The input is the decision result sent from the server. The results are visually displayed on the terminal, prompting the user to take the necessary action. The output is a result message presented to the user, which includes information such as "Seal has been confirmed." The user then decides on their next action based on this.

[0661] (Application Example 1)

[0662] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0663] In daily operations, verifying the presence of a seal on a document is a time-consuming and laborious process. This invention aims to efficiently identify the seal impressions on coupons and membership cards in physical stores, reduce the time required for seal verification, and prevent fraudulent use.

[0664] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0665] In this invention, the server includes means for analyzing the visible seal impression contained in the application form using an image processing device, identifying the type of seal impression, and converting the symbols within the seal impression into character data; means for recording the character data in an information storage device that stores data for each organization; and means for comparing the seal impression of a newly submitted application form with the stored information in the information storage device and determining whether the seal impression is appropriate according to predetermined standards. This enables automatic recognition and verification of coupons and membership cards in physical stores.

[0666] A "visible impression" is an impression that is imprinted in a form that is visible on paper or a digital screen.

[0667] An "image processing device" is an electronic device used to analyze, convert, and identify captured image data.

[0668] A "symbol" refers to an identifiable character element, such as an alphabet or number, included within the seal impression.

[0669] "Character data" refers to information that represents analyzed symbols in digital format.

[0670] An "information storage device" is a storage system for securely storing digital data over long periods of time.

[0671] "Storing data by organization" refers to a method of individually recording and storing data associated with different groups or corporations.

[0672] "Automatic recognition" is the ability of a machine or software to identify specific patterns or information without human intervention.

[0673] "Means of judgment" refers to a method or process of evaluating whether something is appropriate or not using specific criteria based on the information that has been entered.

[0674] This invention is a system for the automatic recognition and verification of coupons and membership cards within a store. The user uses a smart device to capture a visible imprint of the presented coupon. The captured image data is transmitted to a server in real time.

[0675] The server uses an image processing device to extract visible seal impressions from received images and analyzes the symbols contained within those impressions. A generative AI model is used for this analysis, automatically identifying the type of seal impression and converting the symbols into character data. The converted character data is recorded in information storage devices for each relevant organization.

[0676] Next, the server compares the text data of the newly submitted coupon with information already stored in the information storage device. This comparison determines whether the coupon is valid according to predetermined criteria. The result is immediately output to the terminal's display device and notified to the user. For example, if the coupon is valid, it will display "20% off applied."

[0677] As a concrete example, the generating AI model recognizes and processes a seal impression based on a prompt message such as, "Analyze the seal impression in this image, extract text information, and determine its validity." Based on this prompt message, the AI ​​performs an appropriate analysis, enabling the entire system to operate efficiently.

[0678] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0679] Step 1:

[0680] The user uses a smart device to capture a visible imprint on the presented coupon. This captured image becomes the input. The captured image data is then sent directly to the server.

[0681] Step 2:

[0682] The server analyzes the received image data using an image processing device. Here, data processing is performed to extract visible seal impressions from the image. The extracted seal impressions become the output, and the process proceeds to the next stage.

[0683] Step 3:

[0684] The server utilizes a generation AI model to analyze the extracted seal impressions. The input is the extracted seal impressions, and it performs data calculations to recognize the symbols contained within the impressions and convert them into character data. This character data becomes the output and is sent to the information storage device.

[0685] Step 4:

[0686] The server records character data in an information storage device and stores it in the database of the relevant organization as needed. The input is converted character data, and the output is recorded data.

[0687] Step 5:

[0688] The system compares the text data of newly submitted coupons with existing data. The server uses predetermined criteria to evaluate the input data and performs data calculations to assess the validity of the coupons. The results of the validity assessment are then output.

[0689] Step 6:

[0690] The server sends the judgment result to the terminal's display device. The input here is the judgment result of the suitability, and the output notified to the user is the display screen. Specifically, if the validity is confirmed, the application of discounts, etc., will be clearly indicated.

[0691] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0692] This invention is a system that automates the verification of seals on application forms and provides feedback that takes user emotions into consideration. This system operates by combining image processing technology that identifies the type and characters of the seals with an emotion engine that recognizes user emotions.

[0693] First, the user digitally scans the application form submitted by the company and uploads it to the server. The server receives this data and uses an image processing device to detect and analyze the seal portion of the application form. Here, the shape of the seal and the text information within the seal impression are extracted and stored in a database as text data.

[0694] Next, newly submitted application forms are processed in the same manner and compared with accumulated data to automatically evaluate whether the seal impression conforms to the regulations. The emotion engine analyzes the user's facial expressions and voice when the user checks the results to determine their emotional state. As a result, for example, if the user is tense, the device uses relaxing interfaces and notifications to reduce stress.

[0695] Furthermore, convenience is enhanced by providing quick and simple feedback to users who are fully satisfied. This system not only streamlines the stamping verification process but also realizes a new interaction model to improve the user experience.

[0696] For example, if the emotion engine detects disappointment when a user reviews a stamped document, the server displays a detailed error explanation and support contact information on the screen. This allows the user to intuitively understand what action to take next. In this way, the system provides advanced accessibility and usability, enabling customized services tailored to individual users.

[0697] The following describes the processing flow.

[0698] Step 1:

[0699] The user scans the application form submitted by the company as digital data and uploads the data to the server. This allows the application form to be incorporated into the system.

[0700] Step 2:

[0701] The server analyzes the received application form data, automatically detects the stamped area using an image processing device, and extracts the image data by cropping the corresponding portion.

[0702] Step 3:

[0703] The server sends the extracted image data of the seal impression to an AI model that analyzes the type of seal impression (round seal, square seal, etc.) and the text information within the impression, and converts it into text data.

[0704] Step 4:

[0705] The acquired text data is organized by company on the server and recorded in a database. This data is used as reference data in the subsequent seal verification process.

[0706] Step 5:

[0707] When a new application form is submitted, the server repeats the same process, comparing the stored text data with the new data. This determines whether the seal is genuine.

[0708] Step 6:

[0709] As soon as a judgment is made regarding the legitimacy of the seal impression, the terminal activates an emotion engine to analyze the user's face and voice in real time and recognize the user's emotional state.

[0710] Step 7:

[0711] Based on the analysis results of the emotion engine, the server generates feedback tailored to the user's emotions and displays it on the device. This feedback can include, for example, gentle voice guidance to alleviate tension or help information when more detailed explanations are needed.

[0712] Step 8:

[0713] The device notifies the user of the final feedback and, if necessary, informs them that visual inspection is not required. This process improves the user experience and increases operational efficiency.

[0714] (Example 2)

[0715] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] The present invention aims to solve the problem of improving the user experience by streamlining the process of verifying seals included in application documents and providing feedback that takes user emotions into consideration. Specifically, it aims to reduce the psychological burden on users when receiving feedback on the results in a system that automatically determines the authenticity of seals.

[0717] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0718] In this invention, the server includes means for analyzing the seal impression contained in the application document with an image processing device to identify the type of seal impression and convert the marks within the seal impression into data; means for recording the data in an information recording device that stores data for each organization; means for comparing the seal impression of a newly submitted application document with the stored data in the information recording device and automatically determining whether the seal impression is appropriate according to predetermined criteria; means for analyzing the user's emotions when presenting the judgment result using an emotion recognition device that acquires the user's emotions; and means for providing feedback to a display device that corresponds to the user's state based on the analysis results. This improves the accuracy and efficiency of seal impression verification and makes it possible to create an environment in which users can accept the results with peace of mind.

[0719] An "application document" refers to a formal document created and submitted for various procedures or transactions.

[0720] "Seal impression" refers to the shape or mark left on paper or electronic documents by an imprinted seal or stamp.

[0721] An "image processing device" refers to hardware or software used to analyze, convert, and process information on digital images.

[0722] An "information recording device" refers to a computer system or database used for long-term data storage.

[0723] An "emotion recognition device" refers to a system that possesses technology to analyze a person's facial expressions and voice to estimate their emotional state.

[0724] A "display device" refers to a screen or monitor used to visually display information from a computer or other electronic device.

[0725] "Automated discrimination" refers to the process by which machines or software analyze data and information and make decisions without human intervention.

[0726] In this embodiment of the invention, the analysis of seals included in application documents and the provision of feedback that takes into account the user's emotions are automated.

[0727] Users scan application documents digitally and upload them to the server. The server uses an image processing device to analyze the received data. This device uses libraries such as OpenCV and TensorFlow to analyze and identify the shape of seals and marks. The processed data is registered in an information recording device for each organization and stored for future comparison.

[0728] Next, the server compares the newly submitted seal impression with an existing database. This comparison process utilizes machine learning models, such as TensorFlow, to perform highly accurate analysis. Once the determination is complete, the terminal displays the results to the user.

[0729] The device analyzes the user's facial expressions via an emotion recognition device, using the camera and voice input. This analysis estimates the user's emotional state, and to provide feedback tailored to the user's emotions, relaxing messages and necessary support information are displayed on the screen. This feedback aims to reduce the user's psychological burden.

[0730] As a concrete example, if the emotion recognition device detects disappointment when the user checks the stamping result, the server can display a detailed error explanation and contact information on the terminal. This helps the user intuitively understand what action to take next. An example of a prompt using a generative AI model is, "Please check the stamping on the application form and display feedback on the screen that corresponds to the user's emotion." This enables an efficient and intuitive user experience.

[0731] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0732] Step 1:

[0733] The user scans the application document digitally and uploads it to the server. The input is the scanned image file, and the output is the data format stored on the server. This procedure converts the physical document into digital data, ready for subsequent processing.

[0734] Step 2:

[0735] The server receives the uploaded image data and uses an image processing device to identify the seal impression. The input is scanned image data, and the output is data with the seal impression extracted. Here, the OpenCV library is used to perform edge detection and contour extraction to determine the location of the seal impression within the image.

[0736] Step 3:

[0737] The server analyzes the detected seal impression data, identifies characters and shapes, and converts them into text data. The input is image data of the seal impression, and the output is text data. Using OCR technology, it reads the character information within the image and stores the data in an information recording device for each organization.

[0738] Step 4:

[0739] The server compares newly submitted seal impression data with existing database data. Input is the old and new seal impression text data, and output is a matching score and classification result. Machine learning libraries such as TensorFlow are used to perform automatic classification according to defined criteria.

[0740] Step 5:

[0741] The device uses an emotion recognition device to analyze the user's emotions in order to present the discrimination results to the user. The input is the user's facial expressions and voice, and the output is the estimated emotional state. During this process, the camera and microphone are used to collect real-time input, and the AI ​​model infers the emotions.

[0742] Step 6:

[0743] The device displays feedback tailored to the user's state based on the results of emotion recognition. Input is the emotional state and the recognition result, while output is appropriate feedback messages and on-screen instructions. It provides reassuring messages, relaxing interfaces, or support information, taking actions to reduce the user's psychological burden.

[0744] (Application Example 2)

[0745] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0746] Traditionally, the process of verifying signatures on application forms has often been performed manually, which is not only prone to misrecognition and time-consuming, but also lacks feedback that takes user emotions into consideration. This can potentially detract from the user experience. The present invention aims to improve the user experience by automating the signature verification process and optimizing feedback by analyzing user emotions.

[0747] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0748] In this invention, the server includes means for analyzing the seal impression contained in the application form with an image processing device to identify the type of seal impression and convert the characters in the seal impression into digital data; means for recording the digital data in a database that stores data for each organization; means for comparing the seal impression of a newly submitted application form with the stored information in the database and determining whether the seal impression is appropriate according to predetermined standards; means for displaying the determination result on a display device; means for analyzing the user's emotional state using an emotion engine and providing an interface based on the analysis result; and means for automatically adjusting the interface according to the customer's emotions and providing elements that promote relaxation. As a result, the process of confirming the seal impression is automated, and flexible feedback according to the user's emotions is possible, improving the user experience.

[0749] An "application form" is a document that a user fills out and submits when entering into a contract for purchasing goods or using a service.

[0750] "Seal impression" refers to image data that includes the shape of a stamped seal and the text information contained within it.

[0751] An "image processing device" is a device that has a computing mechanism for analyzing digital images and extracting various features.

[0752] "Digital data" refers to data obtained by converting analog information into a digital format.

[0753] A "database" is a collection of information that is systematically stored and made retrieval and utilization efficient.

[0754] A "standard" is a benchmark or criterion that serves as a reference for making judgments or evaluations.

[0755] An "emotion engine" is software or a system equipped with an algorithm for analyzing and determining a user's emotions.

[0756] A "display device" is a device that visually displays information output from a computer on a screen.

[0757] An "interface" is a point of contact or means that enables communication between a user and a computer system.

[0758] "Elements that promote relaxation" refer to various means and techniques designed to alleviate the user's tension and anxiety and guide their mind and body into a relaxed state.

[0759] This invention comprises a system that automates the verification of seals on application forms and provides feedback that takes into account the user's emotions. A specific embodiment is shown below.

[0760] First, the user uses a terminal installed in the store to scan the application form required for purchase or contract. The terminal is equipped with a high-precision scanning function to accurately capture the seal impression on the application form. Image processing using OpenCV is performed on this terminal, and the type of seal impression and the text information inside are converted into digital data.

[0761] Next, the converted digital data is uploaded to a server. The server runs a Django-based backend system, and the data is stored in a database operated by each organization. Simultaneously, past seal impression data and new seal impression data are compared within the database, and the system automatically determines whether the seal impression is appropriate according to the regulations. This determination result is immediately displayed on the terminal's screen.

[0762] Furthermore, the server incorporates an emotion engine that analyzes customer facial expressions. The user's facial image, captured by the device's camera, undergoes real-time emotion analysis using the Microsoft Azure Face API or Google Cloud Vision AI. If the user is feeling tense or anxious, the interface automatically adjusts, displaying elements that promote relaxation. These relaxation elements include soft color backgrounds and the playback of calming music.

[0763] For example, when a user checks the results of signing an application form, if the emotion engine detects a stress response from the user's face, the system will gently display intuitive operation guides and take actions to reduce stress. This allows the user to clearly understand what action to take next.

[0764] An example of a prompt when using a generative AI model is, "Analyze customer facial expression data in real time and create an interface that reduces tension."

[0765] Thus, the present invention significantly improves the efficiency of the stamping verification process, enables flexible feedback that responds to customer emotions, and supports the provision of a better user experience.

[0766] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0767] Step 1:

[0768] The user uses a terminal installed in the store to scan the application form. The terminal is equipped with a camera for image processing, which captures the seal impression on the application form. The input is a paper application form, and the output is digital image data.

[0769] Step 2:

[0770] The terminal uses OpenCV to process captured image data, detecting and cropping the position of the seal impression. Here, the shape of the seal impression and internal text information are extracted from the image data and converted into digital data. The input is a scanned image, and the output is digital data that retains the characteristics of the seal impression.

[0771] Step 3:

[0772] The terminal uploads the converted digital data to the server. The server processes the received data using a Django-based platform and stores it in a database structured by organization. The input here is the seal impression data, and the output is the information recorded in the database.

[0773] Step 4:

[0774] The server compares newly uploaded data with existing seal impression data in the database. This process executes a data comparison algorithm based on established procedures. The input consists of the new seal impression data and the stored data in the database, while the output is the judgment result regarding the appropriateness of the seal impression.

[0775] Step 5:

[0776] The terminal receives the decision result from the server and displays it on the screen. In this case, the output indicates whether the decision was appropriate or not, and this is visually fed back to the user.

[0777] Step 6:

[0778] The device captures the user's facial expressions with its camera, and the server analyzes this data using an emotion engine. APIs used include Microsoft Azure Face API and Google Cloud Vision AI. The input is a user's facial image, and the output is their emotional state.

[0779] Step 7:

[0780] The server, based on the analyzed emotional state, prepares and sends a relaxation-promoting interface to the terminal. The input is the user's emotional state, and the output is the generated display interface (changes in color scheme and music). The user interface is dynamically adjusted based on the actions taken.

[0781] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0782] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0783] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0784] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0785] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0786] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0787] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0788] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0789] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0790] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0791] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0792] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0793] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0794] 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.

[0795] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0796] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0797] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0798] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0799] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0800] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0801] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0802] The following is further disclosed regarding the embodiments described above.

[0803] (Claim 1)

[0804] A means for analyzing the seal impression contained in the application form using an image processing device, identifying the type of seal impression, and converting the characters within the seal impression into text data,

[0805] A means for recording the aforementioned text data in a database that stores data for each company,

[0806] A means for comparing the seal impression on a newly submitted application form with the stored data in the aforementioned database and determining whether the seal is appropriate according to predetermined standards,

[0807] A means for displaying the judgment result on an output device,

[0808] A system that includes this.

[0809] (Claim 2)

[0810] The system according to claim 1, wherein the image processing device automatically detects the position of the seal impression and crops the detected seal impression.

[0811] (Claim 3)

[0812] The system according to claim 1, wherein the output device provides means for notifying the user whether a visual inspection is necessary.

[0813] "Example 1"

[0814] (Claim 1)

[0815] A means for analyzing the seal impression contained in the application form using an image processing device, identifying the shape and type of the seal impression, and converting the contents of the seal impression into text data,

[0816] means for recording the aforementioned text data in a storage device that stores it for each organization,

[0817] A means of analyzing extracted text data using an artificial intelligence model and storing the generated information,

[0818] A means for comparing the seal impression of a newly submitted application form with the stored information in the aforementioned storage device and determining whether the seal is appropriate according to predetermined standards,

[0819] A means for displaying the judgment result on a display device,

[0820] A system that includes this.

[0821] (Claim 2)

[0822] The system according to claim 1, wherein the image processing device automatically detects the position of the seal impression and comprises means for cropping the detected seal impression.

[0823] (Claim 3)

[0824] The system according to claim 1, wherein the display device comprises means for notifying the user whether or not a confirmation procedure is necessary.

[0825] "Application Example 1"

[0826] (Claim 1)

[0827] A means for analyzing the visible seal impression contained in the application form using an image processing device, identifying the type of the seal impression, and converting the symbols within the seal impression into character data,

[0828] Means for recording the aforementioned character data in an information storage device that stores the data for each organization,

[0829] A means for comparing the seal impression on a newly submitted application form with the stored information in the information storage device and determining whether the seal is appropriate according to predetermined standards,

[0830] Means for outputting the aforementioned determination result to a display device,

[0831] A means of automatically verifying the validity of a seal impression by photographing the visible seal impression,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, wherein the image processing device includes means for automatically identifying the position of a visible seal impression and for cropping the identified seal impression.

[0835] (Claim 3)

[0836] The system according to claim 1, wherein the display device includes means for notifying the operator whether or not it is necessary to confirm the view.

[0837] "Example 2 of combining an emotion engine"

[0838] (Claim 1)

[0839] A means for analyzing the seal impression contained in the application document using an image processing device, identifying the type of seal impression, and converting the marks within the seal impression into data,

[0840] Means for recording the aforementioned data in an information recording device that stores the data for each organization,

[0841] A means for comparing the seal impression of a newly submitted application document with the stored data in the information recording device and automatically determining whether the seal impression is appropriate according to predetermined standards,

[0842] A means for outputting the judgment result to a display device,

[0843] A means for analyzing the user's emotions when presenting the judgment result, using an emotion recognition device that acquires the user's emotions,

[0844] A means for providing feedback to a display device that corresponds to the user's state based on the analysis results,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, wherein the image processing device has means for automatically detecting the position of the seal impression and cropping the detected seal impression.

[0848] (Claim 3)

[0849] The system according to claim 1, wherein the display device has means for notifying the user whether or not visual confirmation is necessary.

[0850] "Application example 2 when combining with an emotional engine"

[0851] (Claim 1)

[0852] A means for analyzing the seal impression contained in the application form using an image processing device, identifying the type of seal impression, and converting the characters within the seal impression into digital data,

[0853] A means for recording the aforementioned digital data in a database that is stored for each organization,

[0854] A means for comparing the seal impression on a newly submitted application form with the stored information in the aforementioned database and determining whether the seal is appropriate according to predetermined standards,

[0855] A means for displaying the judgment result on a display device,

[0856] A means for analyzing the user's emotional state using an emotion engine and providing an interface based on the analysis results,

[0857] A means of automatically adjusting the interface according to the customer's emotions and providing elements that promote relaxation,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, wherein the image processing device is a means for automatically detecting the position of the seal impression and cropping the detected seal impression.

[0861] (Claim 3)

[0862] The system according to claim 1, wherein the display device includes means for notifying the user of the need for a visual examination. [Explanation of symbols]

[0863] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for analyzing the visible seal impression contained in the application form using an image processing device, identifying the type of the seal impression, and converting the symbols within the seal impression into character data, Means for recording the aforementioned character data in an information storage device that stores the data for each organization, A means for comparing the seal impression on a newly submitted application form with the stored information in the information storage device and determining whether the seal is appropriate according to predetermined standards, Means for outputting the aforementioned determination result to a display device, A means of automatically verifying the validity of a seal impression by photographing the visible seal impression, A system that includes this.

2. The system according to claim 1, wherein the image processing device includes means for automatically identifying the position of a visible seal impression and for cropping the identified seal impression.

3. The system according to claim 1, wherein the display device includes means for notifying the operator whether or not it is necessary to confirm the view.

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