system

Abstract

We provide the system. [Solution] A means of acquiring the seal impression on an application form as a digital image using an image input device, A means of using an image recognition device that identifies the type of seal impression from the aforementioned digital image, A means for extracting character information from the aforementioned digital image using optical character recognition technology, Means for storing the identified type of seal and extracted character information in a database, A means of using a control device that compares the contents of the application form with the information in the database, A means for automatically verifying the seal impression on the application form based on the aforementioned verification results and displaying the results, A system that includes this.

Description

Technical Field

[0004] , , , ,

[0005] , , , ,

[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 the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, the confirmation of the seal on a company's application form is often done manually, and the process requires a great deal of time and labor. In addition, it particularly takes time to confirm whether the type of seal and the characters within the seal impression match correctly. Furthermore, if continuous data confirmation is not performed, manual confirmation is required again when re-applying from the same company, which poses a problem in business efficiency. The object of this invention is to solve these problems and perform the seal confirmation process efficiently and accurately.

Means for Solving the Problems

[0005] This invention utilizes an image input device to acquire the stamp on an application form as a digital image, and an image recognition device to identify the type of stamp. Furthermore, optical character recognition technology is used to extract character information contained in the stamp, and this data is stored in a database. Newly received application forms are automatically compared with past database entries to verify the stamp's accuracy. Using these results, application forms are automatically approved, eliminating the need for visual verification and providing a system that improves operational efficiency.

[0006] An "image input device" is a device used to acquire images in digital format.

[0007] A "digital image" is visual information represented in a format that can be processed by a computer.

[0008] An "image recognition device" is a device that analyzes image data and has the function of identifying specific patterns or features.

[0009] "Optical character recognition technology" is a technology that analyzes characters within an image and converts them into text data.

[0010] A "database" is a system for organizing large amounts of data and keeping it in a state where it can be efficiently searched and used.

[0011] A "control device" is a device or function that controls data processing and the execution of functions within a system.

[0012] "Matching" is the process of checking for similarities and matches between different datasets.

[0013] A "control device" is a device or equivalent that manages the operation of each function of a system.

[0014] "Automatic" refers to operating based on pre-set processes or conditions without human intervention. [Brief explanation of the drawing]

[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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of 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.

Embodiments for Carrying Out the Invention

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

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

[0018] In the following embodiments, the numbered 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), etc.

[0019] In the following embodiments, the numbered 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, the numbered 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, etc.

[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] The system according to the present invention is for automating the verification of seals on paper application forms. It performs a series of steps, from digitizing seals using an image input device, to recognition, storage in a database, verification, and display of results. This makes it possible to significantly reduce the amount of manual verification required while ensuring accuracy.

[0037] In system operation, users first acquire image data of the stamped portion of the application form by digitally scanning or photographing it. This image data is transmitted to the server via a terminal. The server processes the received image with an image recognition device to determine the type of stamp and converts the character information within the stamp impression into text data using optical character recognition technology. The converted information is immediately stored in a database and accumulated as stamp data for each company.

[0038] Next, when a new application form is received, the terminal sends a verification request to the server based on the application details. The server compares the newly acquired stamp data with existing data in the database to determine if they match. This result is quickly returned to the terminal, and the user can receive the verification result. If they match, the application form is automatically approved, and the business process proceeds quickly. On the other hand, if they do not match, the user is notified, and reconfirmation or correction is made as necessary.

[0039] For example, consider a scenario where a company submits a contract application for a new service. When the user scans the application and sends it to the server, the server immediately analyzes the type of seal and text information and stores it in a database. The next time the same company submits an additional service application, the terminal retrieves the seal data from the server database and checks for a match with the previous data. If a match is confirmed, the terminal automatically approves the application, and the user experiences the speed and accuracy of the process.

[0040] Thus, the present invention significantly streamlines the process of verifying seals, reducing the risk of errors and shortening working hours.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user obtains a digital image of the stamped portion of the application form using a scanner or camera. The resulting image is saved on the device.

[0044] Step 2:

[0045] The terminal transmits images acquired by the user to the server through the system interface. The transmitted images arrive at the server in digital format.

[0046] Step 3:

[0047] The server first passes the received stamped image to an image recognition device to identify the type of stamp (round, square, etc.). Subsequently, it uses optical character recognition technology to analyze the string of characters within the stamp impression and convert it into text data.

[0048] Step 4:

[0049] The server stores the analyzed seal type and character information in a database. This allows for the accumulation of seal data for each company, preparing for future matching.

[0050] Step 5:

[0051] When a new application form arrives, the terminal sends a verification request to the server based on that information. This prepares the system for a smooth comparison between the data in the database and the new application data.

[0052] Step 6:

[0053] The server meticulously compares the database records with the newly submitted stamp data to determine if they match. If a complete match is confirmed for the type of stamp and the character information, automatic approval is possible.

[0054] Step 7:

[0055] The terminal receives the matching results sent from the server and displays the results to the user. If a match is found, the user receives a notification that approval is complete. If a mismatch occurs, a warning is displayed, and the user is prompted to manually re-verify or correct the information.

[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] The process of verifying seal impressions in paper records has traditionally relied heavily on visual inspection, resulting in a time-consuming process prone to human error. Furthermore, ensuring accuracy in handling seal types and textual information often led to increased workload.

[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 acquiring a seal impression as a digital image from a paper record using a communication device, means for analyzing the characteristics of the seal impression from the digital image using an information processing device, and means for converting character data from the digital image by applying optical character recognition technology. This enables automatic analysis of the seal impression and accurate data conversion.

[0061] A "communication device" is a device used to acquire digital images from paper records and transmit them to a server.

[0062] An "information processing device" is a device used to analyze and identify the characteristics of a seal impression from a digital image.

[0063] "Optical character recognition technology" is a technology that converts character information within digital images into text data.

[0064] A "memory device" is a device for storing the characteristics of the analyzed seal impression and the converted character data.

[0065] A "computer" is a device that compares application details with information stored in memory and outputs the results.

[0066] The "update function" is a function that updates data stored on a storage device for each organization.

[0067] This invention is a system that improves operational efficiency and accuracy by automating the verification of seal impressions on paper application forms. First, the user uses a communication device to digitally scan or photograph the seal portion of the application form to obtain image data. This image data is transmitted from the terminal to the server via a secure communication protocol.

[0068] The server processes the received digital image using an information processing device. This processing is performed using image recognition software and includes a process of extracting the outline of the seal impression and identifying its characteristics. Optical character recognition technology is also applied to convert the character information within the seal impression into text data. This data conversion makes it possible to accurately acquire information from paper media as digital data.

[0069] The converted data is stored in a storage device. This stored data can then be updated with company or individual signature information. When a new application form is received, the terminal requests the server to compare it with existing information. The server uses a computer to compare the information in the database and determines whether there is a match or not.

[0070] To understand this system concretely, let's consider a scenario where a company submits a contract application for a new service. The user scans the application and sends the image data to the server. The server immediately analyzes the image, digitizes the seal data and text information, and stores it. The next time the same company submits an application for an additional service, the terminal retrieves the past seal data from the server's database and performs a comparison. This automates the processing of application forms, dramatically improving operational efficiency.

[0071] An example of a prompt to input into a generating AI model is, "Please tell me how to implement a system that digitizes the stamps on paper application forms, recognizes and verifies them, and automatically approves them." This prompt allows for the efficient acquisition of specific implementation methods and technical approaches.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user prepares a paper application form and uses a communication device to digitally scan or photograph the stamped portion. This operation results in the input of image data of the application form. This acquired image data is then transmitted to the server via the terminal.

[0075] Step 2:

[0076] The server processes the received image data using an information processing device. Specifically, it first analyzes the outline of the seal impression using image recognition software and identifies its characteristics. An outline detection algorithm is applied to the input image data, and the type of seal impression is obtained as output. This identification is important to ensure the accuracy of the information.

[0077] Step 3:

[0078] The server uses optical character recognition (OCR) technology to convert character information within image data into text data. This process is performed by an OCR engine, and the input is pre-processed image data. The output is digital text of the character information contained in the seal impression. This text data is then used for subsequent database storage.

[0079] Step 4:

[0080] The server stores the analyzed seal characteristics and converted character data in storage. The input to this storage process is text data, and the output is structured information in a database. This information forms the basis for future matching operations.

[0081] Step 5:

[0082] The terminal sends a verification request to the server based on the newly received application form. The input here is the information from the new application form, and the output is an instruction for the server to perform a database verification accordingly.

[0083] Step 6:

[0084] The server retrieves previously matched seal impression data from the current database and compares it with the new data. The input consists of existing information in the database and the new data, and the output is the result of a match or mismatch determination. This comparison is performed using a sophisticated algorithm.

[0085] Step 7:

[0086] The server sends the matching results to the terminal and requests confirmation from the user. If the results match, the output triggers an automated approval process. If there is a mismatch, the user is warned, and a re-evaluation or manual verification process is initiated.

[0087] (Application Example 1)

[0088] 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."

[0089] Traditionally, the process of verifying customer signatures on application forms and loyalty card usage requests at physical stores has been done manually, which is time-consuming, labor-intensive, and prone to human error. This reduces the efficiency and reliability of the process, hindering improvements in customer service quality. There is a need for a system that can solve this problem and perform quick and accurate signature verification on-site.

[0090] 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.

[0091] In this invention, the server includes means for acquiring the stamping of a document as a digital image using an image acquisition device, means for using an image analysis device to identify the type of stamping from the digital image, and means for extracting character information from the digital image using optical information recognition technology. This makes it possible to verify and approve stamping in real time using a smart device in a physical store.

[0092] An "image acquisition device" is a hardware device used to acquire the stamped portion of a document as a digital image.

[0093] An "image analysis device" is a device that performs image processing to identify the type of seal impression from acquired digital images.

[0094] "Optical information recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0095] An "information recording device" is a device that includes a database for recording the type of stamped item identified and the extracted character information.

[0096] A "computational device" is a system that includes a processor for comparing the contents of a document with data in an information recording device.

[0097] A "smart device" is a portable electronic device used to verify stamping in real time at physical stores.

[0098] This invention is a system for streamlining the verification of stamps on paper application forms and point card usage applications at physical stores. When a customer submits an application form, store staff use a smart device to acquire the stamped portion as a digital image. Specifically, the stamp is scanned using an image acquisition device (smartphone camera). The server receives this image and identifies the type of stamp using an image analysis device (using OpenCV). Furthermore, optical information recognition technology (using OCR software such as Tesseract) is used to extract the character information contained within the stamp.

[0099] This information is stored in an information recording device. The server also uses a computing device to compare the stamped data on the new application form with existing data in the database to determine if they match. If the matching results are correct, the application form is immediately approved, and the confirmation result is displayed to the user on their smart device. If there is a mismatch, a notification is sent to the smart device, prompting the user to perform additional verification.

[0100] As a concrete example, when a new member registers at a restaurant, the customer submits an application form, and a staff member scans the signature using a smart device. The data is immediately processed on the server, allowing the process to proceed quickly. This system enables quick and efficient on-site signature verification, contributing to improved customer service quality.

[0101] As an example of a prompt for the generating AI model, enter the following: "Please scan the stamped portion of the application form below and check if it matches the database. The procedure is to activate the camera, recognize the captured image data, extract the text information, and send it to the server for verification. Please let me know the result."

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The user submits an application form at the store, and the terminal (smartphone) uses its camera to scan the stamped portion of the application form. The input is a stamp on paper, and the output is a digital image file. The terminal prepares to send the digital image to the server.

[0105] Step 2:

[0106] The server passes the digital image received from the terminal to image analysis software (OpenCV). The input is digital image data, and the output is the type of stamp identified. The server analyzes the stamps in the image and identifies their type.

[0107] Step 3:

[0108] The server extracts character information from the identified stamp data using OCR software (Tesseract). The input is image data of the stamp. The output is character information in text format. The server registers the acquired character information in a database.

[0109] Step 4:

[0110] The server compares existing stamp data in the database with newly acquired data. The input consists of character information on the server and existing information in the database. The output is the match or mismatch result. The server compares the data and generates the result.

[0111] Step 5:

[0112] The server sends the matching results to the terminal. The input is the matching result data, and the output is the result display on the user's terminal screen. The terminal displays the match / mismatch results to the user and guides them to the next step.

[0113] Step 6:

[0114] Based on instructions issued by the device, the user performs actions such as manual verification or resubmission in case of discrepancies. Input is the information displayed on the device, and output is the user's response. The user takes the necessary actions.

[0115] 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.

[0116] The system according to the present invention aims to improve the efficiency of application form processing. In addition to existing technologies such as image input devices, image recognition devices, optical character recognition technology, and database matching, it combines an emotion engine to enhance the user experience. This system can accurately verify the seal impression on application forms and recognize the user's emotional state in real time, adjusting its response accordingly.

[0117] First, the user obtains an image of the seal impression on the application form and sends it to the server via their terminal. On the server, an image recognition device identifies the type of seal impression, and optical character recognition technology converts the character information into text data. This information is stored in a database and centrally managed as seal impression data for each company.

[0118] When a new application is received, the terminal sends the application data to the server. Simultaneously, the user's voice and facial expression data are analyzed by the emotion engine. The server then compares the new data with past stamp data in the database to determine if there is a match. Furthermore, the user's emotional state, as analyzed by the emotion engine, is used to customize the response. For example, if the user indicates feelings of discomfort or confusion, the terminal immediately provides operational guidance or additional support.

[0119] For example, when a company submits an application, if the user experiences stress, the system detects the user's emotions and displays simpler, easier-to-understand guides in the interface. Furthermore, while the signature verification process is underway, the emotion engine continuously monitors the user's emotional state and dynamically takes action to reduce unnecessary stress.

[0120] Thus, the present invention provides a system that improves both operational efficiency and user experience by streamlining the conventional stamping confirmation process while simultaneously enabling flexible responses tailored to the user's emotional state.

[0121] The following describes the processing flow.

[0122] Step 1:

[0123] The user obtains the application form as image data using a scanner or camera. The obtained image is then saved to the device.

[0124] Step 2:

[0125] The device sends images acquired by the user to the server. During transmission, audio and facial expression data are also collected simultaneously for emotion analysis.

[0126] Step 3:

[0127] The server processes the received stamped image using an image recognition device to identify the type of stamp. It also uses optical character recognition technology to convert the character information within the stamped image into text data.

[0128] Step 4:

[0129] The server stores the identified type of seal and extracted character information in a database and updates the seal data for each company.

[0130] Step 5:

[0131] The device inputs simultaneously transmitted audio and facial expression data into an emotion engine to analyze the user's emotions. This analysis identifies the user's current emotional state.

[0132] Step 6:

[0133] The server compares the new application data with the stamp data stored in the database. If a match is found, the application is automatically approved. If there is a mismatch, a more detailed re-verification will be required.

[0134] Step 7:

[0135] Based on the analysis results of the emotion engine, the device flexibly changes its response if the user is experiencing stress, and displays operation guides and support messages on the screen.

[0136] Step 8:

[0137] Users can receive approval results through their terminal and, if necessary, take additional actions by following the guidance provided by the system.

[0138] This series of steps allows the system to efficiently verify signatures while also supporting user emotions and providing an excellent user experience.

[0139] (Example 2)

[0140] 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".

[0141] Conventional application processing systems often involved manual verification of signatures, leading to inefficient processing and frequent human errors. Furthermore, a lack of consideration for user feelings sometimes resulted in confusion and dissatisfaction. Additionally, achieving highly accurate database management of application forms proved difficult.

[0142] 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.

[0143] In this invention, the server includes means for acquiring electronic images, means for recognizing the type of seal impression, means for storing and comparing information in a database, and means for analyzing the user's emotions and adjusting the interface. This enables rapid and accurate processing of application forms and flexible responses to the user's emotions.

[0144] An "image capture device" is a device used to capture objects or documents in electronic format.

[0145] An "electronic image" is image information that is stored and displayed as digital data.

[0146] A "visual recognition device" is a device that detects and identifies specific shapes and features from electronic images.

[0147] "Character recognition technology" is a technology that electronically extracts handwritten or printed character information and recognizes it as text data.

[0148] An "information storage device" is a device or system for electronically storing and making accessible large amounts of data.

[0149] A "control device" is a device used to manage and instruct specific processes or functions.

[0150] An "emotion analysis device" is a device that analyzes a user's emotional state based on their voice and facial expression data.

[0151] "User interface display" refers to the screens and their arrangement and design that users use to interact with the system.

[0152] This invention provides a system for streamlining application form processing, which can be implemented by combining elements such as an image capture device, a visual recognition device, character recognition technology, an information accumulating device, and an emotion analysis device. The main components are as follows:

[0153] First, the user fills in information on the application form and uses an image capture device to obtain an electronic image of the entire form, including the seal. The terminal temporarily stores this image on the device and then transmits it to the server via the internet.

[0154] On the server, the type of seal is identified from the received electronic image using a visual recognition device. Image processing libraries such as OpenCV and TENSORFLOW® can be used for this process. Next, optical character recognition technology is used to convert the character information within the image into text data. At this stage, Tesseract OCR or Google® Cloud Vision API can be used.

[0155] Next, the server stores the identified type of seal and extracted character information in the information aggregation device. Database systems such as MySQL® and MongoDB can be used. Furthermore, the server compares the contents of the application form with existing data in the information aggregation device to determine if they match. Using SQL queries at this stage allows for efficient matching.

[0156] The terminal collects user voice and facial expression data using an emotion analysis device while the user is operating the system. This can utilize Microsoft® Azure® Emotion API, among others. Based on this data, the user's emotions are analyzed, and the interface display is adjusted as needed.

[0157] As a concrete example, when a user submits an application form, if they have any questions about the procedure, the device will provide appropriate support information based on the sentiment analysis results. This allows the user to proceed with the procedure smoothly without feeling stressed.

[0158] An example of a prompt message might be, "Display support information to optimize the user interface based on the user's emotional state."

[0159] In this way, the present invention automates the application form processing process and responds to user emotions, thereby simultaneously achieving operational efficiency and improved user experience.

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

[0161] Step 1:

[0162] The user takes a picture of the application form using the image capture device on the terminal. The input to this process is the physical application form, and the output is an electronic image stored on the terminal. This image will be used in subsequent processing steps.

[0163] Step 2:

[0164] The terminal sends the acquired electronic image to the server. At this stage, the input is the electronic image, and the output is the transmission of image data to the server. The terminal uploads the image data to the server using a secure protocol (e.g., HTTPS).

[0165] Step 3:

[0166] The server analyzes the received electronic image using a visual recognition device to identify the type of seal. The input is the electronic image sent from the terminal, and the output is data representing the recognized type of seal. This process utilizes OpenCV and TensorFlow for feature extraction and matching.

[0167] Step 4:

[0168] The server extracts character information from electronic images using optical character recognition (OCR) technology. The input is an electronic image, and the output is text data. This process involves analyzing the character portion within the image and converting it into character codes using technologies such as Tesseract OCR.

[0169] Step 5:

[0170] The server stores the identified stamp type and extracted character information in the information accumulator. The input is the stamp type and text data obtained in the previous step, and the output is the data stored in the information accumulator. The server uses a database management system to centrally store the information.

[0171] Step 6:

[0172] The server compares the contents of the application form with the data stored in the data aggregation device. Input consists of newly registered data and existing data, while output is the result of the comparison. The server uses SQL queries to verify data consistency and analyzes the results.

[0173] Step 7:

[0174] The device analyzes the user's voice and facial expression data in real time using an emotion analysis device. In this process, the device acquires voice and facial expression data as input and obtains the analyzed user's emotional state as output. The Emotion API and other similar tools are used for emotion analysis.

[0175] Step 8:

[0176] The server adjusts the user interface display based on the emotional state obtained by the emotion analysis device. The input is the user's emotional state data, and the output is the adjusted screen display. In particular, if the user is showing discomfort or confusion, the terminal's display content is changed to be more intuitive and easy to understand.

[0177] Through these processing steps, this system not only automates the processing of application forms but also enables flexible responses that take into account the user's feelings.

[0178] (Application Example 2)

[0179] 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 device 14 will be referred to as the "terminal."

[0180] While conventional application processing systems are increasingly automated in verifying signatures, they cannot respond to changes in customer emotions in real time, potentially resulting in a diminished user experience. Furthermore, there is a need to improve the quality of customer service, particularly in handling discrepancies in matching results and manual verification. Efficiently managing and updating diverse signature information specific to each company and organization is also crucial.

[0181] 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.

[0182] In this invention, the server includes means for acquiring the seal impression on the application form as a digital image using an image acquisition device, means for identifying the type of seal impression from the digital image using an image analysis device, means for extracting character information using optical character recognition technology, means for using an emotion estimation engine that analyzes the customer's voice and facial expression data, means for storing and comparing the identified information in an information storage system, and means for dynamically providing guidance based on the customer's emotional state. This improves the efficiency of application form processing, enables appropriate responses to customer emotions, and enhances the user experience.

[0183] An "image acquisition device" is a device used to acquire stamps and textual information from application forms and other documents as digital data.

[0184] An "image analysis device" is a device used to identify specific patterns or types from acquired digital images.

[0185] "Optical character recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0186] An "information storage system" is a database system that centrally manages identified stamps and extracted text information, and performs verification and updating as needed.

[0187] An "emotion estimation engine" is software that analyzes customer voice and facial expression data to estimate their emotional state in real time.

[0188] A "control system" is a computer system that compares the contents of an application form with data in the information storage system to determine whether or not they match.

[0189] "A means of dynamically providing guidance" refers to a function that instantly presents the most appropriate actions or support on the interface according to the customer's current emotional state.

[0190] The following describes embodiments for carrying out this invention. The system aims to streamline the processing of application forms and dynamically adjust the interface according to the customer's emotions.

[0191] The server uses an image acquisition device to capture the seal impression on the application form as a digital image. The acquired image is then analyzed by an image analysis device to identify the type of seal impression, and the character information is extracted as text data using optical character recognition technology. This information is stored in a database within the information storage system, and the seal impression information is managed and updated for each company or organization.

[0192] When a customer uses a terminal to submit a new application form, the terminal sends the data to the server. The server uses a matching system to compare the contents of the application form with past information in the database to determine if there is a match.

[0193] Furthermore, the server uses an emotion estimation engine to analyze customer voice and facial expression data in real time to estimate their emotional state. For example, if a customer shows signs of anxiety or stress, the server dynamically provides the terminal with operational guidance and additional support information. This allows customers to proceed with the process appropriately and quickly.

[0194] As a concrete example, in customer service at physical stores, this system allows staff to adjust their responses based on the customer's current emotional state. For instance, by providing a prompt message from the server such as, "We have detected that the customer is dissatisfied. Please suggest an appropriate response," staff can provide more effective service. This improves both the user experience and operational efficiency.

[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 to photograph the stamp on the application form. The digital image acquired by the image acquisition device is sent from the terminal to the server. The input is the digital image of the stamp taken by the user, and the output is the image data transferred to the server.

[0198] Step 2:

[0199] The server uses an image analysis device to analyze the received digital image and identify the type of seal. The identified information is stored in a database. The input is a digital image, and the output is data of the identified type of seal.

[0200] Step 3:

[0201] The server uses optical character recognition (OCR) technology to extract character information from digital images. The extracted character information is stored in a database. The input is a digital image, and the output is character information in text data format.

[0202] Step 4:

[0203] The server uses information stored in the database within the information storage system to compare new application data with past data. The inputs are the new application data and database data, and the output is the comparison result.

[0204] Step 5:

[0205] Voice and facial expression data from the user are collected via the terminal and analyzed by the server's emotion estimation engine. The input is voice and facial expression data, and the output is estimated emotion state data.

[0206] Step 6:

[0207] The server generates and dynamically presents operation guides and appropriate support information to the terminal based on the user's emotional state. The input is estimated emotional state data, and the output is operation guides and support information. This allows the user to receive responses tailored to their emotions.

[0208] Step 7:

[0209] Prompt messages are generated via a generative AI model and provided to the user or device. This allows the user interface to be adjusted in real time. The input is data for the generative AI model, and the output is the prompt message.

[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 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 the following. 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 indicated 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] The system according to the present invention is for automating the verification of seals on paper application forms. It performs a series of steps, from digitizing seals using an image input device, to recognition, storage in a database, verification, and display of results. This makes it possible to significantly reduce the amount of manual verification required while ensuring accuracy.

[0227] In system operation, users first acquire image data of the stamped portion of the application form by digitally scanning or photographing it. This image data is transmitted to the server via a terminal. The server processes the received image with an image recognition device to determine the type of stamp and converts the character information within the stamp impression into text data using optical character recognition technology. The converted information is immediately stored in a database and accumulated as stamp data for each company.

[0228] Next, when a new application form is received, the terminal sends a verification request to the server based on the application details. The server compares the newly acquired stamp data with existing data in the database to determine if they match. This result is quickly returned to the terminal, and the user can receive the verification result. If they match, the application form is automatically approved, and the business process proceeds quickly. On the other hand, if they do not match, the user is notified, and reconfirmation or correction is made as necessary.

[0229] For example, consider a scenario where a company submits a contract application for a new service. When the user scans the application and sends it to the server, the server immediately analyzes the type of seal and text information and stores it in a database. The next time the same company submits an additional service application, the terminal retrieves the seal data from the server database and checks for a match with the previous data. If a match is confirmed, the terminal automatically approves the application, and the user experiences the speed and accuracy of the process.

[0230] Thus, the present invention significantly streamlines the process of verifying seals, reducing the risk of errors and shortening working hours.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user obtains a digital image of the stamped portion of the application form using a scanner or camera. The resulting image is saved on the device.

[0234] Step 2:

[0235] The terminal transmits images acquired by the user to the server through the system interface. The transmitted images arrive at the server in digital format.

[0236] Step 3:

[0237] The server first passes the received stamped image to an image recognition device to identify the type of stamp (round, square, etc.). Subsequently, it uses optical character recognition technology to analyze the string of characters within the stamp impression and convert it into text data.

[0238] Step 4:

[0239] The server stores the analyzed seal type and character information in a database. This allows for the accumulation of seal data for each company, preparing for future matching.

[0240] Step 5:

[0241] When a new application form arrives, the terminal sends a verification request to the server based on that information. This prepares the system for a smooth comparison between the data in the database and the new application data.

[0242] Step 6:

[0243] The server meticulously compares the database records with the newly submitted stamp data to determine if they match. If a complete match is confirmed for the type of stamp and the character information, automatic approval is possible.

[0244] Step 7:

[0245] The terminal receives the matching results sent from the server and displays the results to the user. If a match is found, the user receives a notification that approval is complete. If a mismatch occurs, a warning is displayed, and the user is prompted to manually re-verify or correct the information.

[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] The process of verifying seal impressions in paper records has traditionally relied heavily on visual inspection, resulting in a time-consuming process prone to human error. Furthermore, ensuring accuracy in handling seal types and textual information often led to increased workload.

[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 acquiring a seal impression as a digital image from a paper record using a communication device, means for analyzing the characteristics of the seal impression from the digital image using an information processing device, and means for converting character data from the digital image by applying optical character recognition technology. This enables automatic analysis of the seal impression and accurate data conversion.

[0251] A "communication device" is a device used to acquire digital images from paper records and transmit them to a server.

[0252] An "information processing device" is a device used to analyze and identify the characteristics of a seal impression from a digital image.

[0253] "Optical character recognition technology" is a technology that converts character information within digital images into text data.

[0254] A "memory device" is a device for storing the characteristics of the analyzed seal impression and the converted character data.

[0255] A "computer" is a device that compares application details with information stored in memory and outputs the results.

[0256] The "update function" is a function that updates data stored on a storage device for each organization.

[0257] This invention is a system that improves operational efficiency and accuracy by automating the verification of seal impressions on paper application forms. First, the user uses a communication device to digitally scan or photograph the seal portion of the application form to obtain image data. This image data is transmitted from the terminal to the server via a secure communication protocol.

[0258] The server processes the received digital image using an information processing device. This processing is performed using image recognition software and includes a process of extracting the outline of the seal impression and identifying its characteristics. Optical character recognition technology is also applied to convert the character information within the seal impression into text data. This data conversion makes it possible to accurately acquire information from paper media as digital data.

[0259] The converted data is stored in a storage device. This stored data can then be updated with company or individual signature information. When a new application form is received, the terminal requests the server to compare it with existing information. The server uses a computer to compare the information in the database and determines whether there is a match or not.

[0260] To understand this system concretely, let's consider a scenario where a company submits a contract application for a new service. The user scans the application and sends the image data to the server. The server immediately analyzes the image, digitizes the seal data and text information, and stores it. The next time the same company submits an application for an additional service, the terminal retrieves the past seal data from the server's database and performs a comparison. This automates the processing of application forms, dramatically improving operational efficiency.

[0261] An example of a prompt to input into a generating AI model is, "Please tell me how to implement a system that digitizes the stamps on paper application forms, recognizes and verifies them, and automatically approves them." This prompt allows for the efficient acquisition of specific implementation methods and technical approaches.

[0262] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0263] Step 1:

[0264] The user prepares a paper application form and uses a communication device to digitally scan or photograph the stamped portion. This operation results in the input of image data of the application form. This acquired image data is then transmitted to the server via the terminal.

[0265] Step 2:

[0266] The server processes the received image data using an information processing device. Specifically, it first analyzes the outline of the seal impression using image recognition software and identifies its characteristics. An outline detection algorithm is applied to the input image data, and the type of seal impression is obtained as output. This identification is important to ensure the accuracy of the information.

[0267] Step 3:

[0268] The server uses optical character recognition (OCR) technology to convert character information within image data into text data. This process is performed by an OCR engine, and the input is pre-processed image data. The output is digital text of the character information contained in the seal impression. This text data is then used for subsequent database storage.

[0269] Step 4:

[0270] The server stores the analyzed seal characteristics and converted character data in storage. The input to this storage process is text data, and the output is structured information in a database. This information forms the basis for future matching operations.

[0271] Step 5:

[0272] The terminal sends a verification request to the server based on the newly received application form. The input here is the information from the new application form, and the output is an instruction for the server to perform a database verification accordingly.

[0273] Step 6:

[0274] The server retrieves previously matched seal impression data from the current database and compares it with the new data. The input consists of existing information in the database and the new data, and the output is the result of a match or mismatch determination. This comparison is performed using a sophisticated algorithm.

[0275] Step 7:

[0276] The server sends the matching results to the terminal and requests confirmation from the user. If the results match, the output triggers an automated approval process. If there is a mismatch, the user is warned, and a re-evaluation or manual verification process is initiated.

[0277] (Application Example 1)

[0278] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0279] In a physical store, the fingerprint confirmation work associated with customer applications, applications for using point cards, etc. has conventionally been performed manually, which takes a great deal of time and labor and there is a risk of human error. This reduces the efficiency and reliability of the process and hinders the improvement of the quality of customer service. There is a need to provide a system that solves this problem and performs fingerprint confirmation quickly and accurately on-site.

[0280] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0281] In this invention, the server includes means for acquiring a fingerprint on a document as a digital image using an image acquisition device, means for using an image analysis device to identify the type of fingerprint from the digital image, and means for extracting character information from the digital image using optical information recognition technology. This makes it possible to perform real-time fingerprint confirmation and approval using a smart device in a physical store. [[ID=!3]]

[0282] The "image acquisition device" is a hardware device for acquiring the fingerprint portion described in a document as a digital image. [[ID=!7]]

[0283] The "image analysis device" is a device that performs image processing for identifying the type of fingerprint from the acquired digital image.

[0284] The "optical information recognition technology" is a technology for analyzing character information from a digital image and extracting it as text data.

[0285] The "information recording device" is a device including a database for recording the identified type of fingerprint and the extracted character information.

[0286] A "computing device" is a system that includes a processor for matching the content of a document with data in an information recording device.

[0287] A "smart device" is a portable electronic device for performing real-time fingerprint verification in a physical store.

[0288] This invention is a system for improving the efficiency of fingerprint verification for paper applications and point card applications in physical stores. When a customer submits an application, a store staff uses a smart device to obtain the fingerprint part as a digital image. Specifically, the fingerprint is scanned using an image acquisition device (the camera of a smartphone). The server receives this image and uses an image analysis device (using OpenCV) to identify the type of fingerprint. Furthermore, optical information recognition technology (using OCR software such as Tesseract) is utilized to extract the character information contained in the fingerprint.

[0289] This information is stored in an information recording device. The server also uses a computing device to compare the fingerprint data of a new application with the existing data in the database and determine whether there is a match. If the comparison result is a match, the application is immediately approved and the confirmation result is displayed on the smart device for the user. If there is a mismatch, a notification is sent to the smart device to prompt the user to perform additional confirmation work.

[0290] As a specific example, when registering as a new member in a restaurant, the customer submits an application, and the staff scans the fingerprint with a smart device. It is immediately processed by the server, and the process proceeds quickly. With this system, on-site fingerprint verification is performed quickly and efficiently, contributing to an improvement in the quality of customer service.

[0291] As an example of a prompt sentence for the generative AI model, input as follows: "Please scan the fingerprint part of the following application and check if it matches the database. The procedure is to activate the camera, recognize the captured image data, extract the character information, send it to the server for comparison, and let me know the result."

[0292] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0293] Step 1:

[0294] The user submits an application form at the store, and the terminal (smartphone) uses its camera to scan the stamped portion of the application form. The input is a stamp on paper, and the output is a digital image file. The terminal prepares to send the digital image to the server.

[0295] Step 2:

[0296] The server passes the digital image received from the terminal to image analysis software (OpenCV). The input is digital image data, and the output is the type of stamp identified. The server analyzes the stamps in the image and identifies their type.

[0297] Step 3:

[0298] The server extracts character information from the identified stamp data using OCR software (Tesseract). The input is image data of the stamp. The output is character information in text format. The server registers the acquired character information in a database.

[0299] Step 4:

[0300] The server compares existing stamp data in the database with newly acquired data. The input consists of character information on the server and existing information in the database. The output is the match or mismatch result. The server compares the data and generates the result.

[0301] Step 5:

[0302] The server sends the matching results to the terminal. The input is the matching result data, and the output is the result display on the user's terminal screen. The terminal displays the match / mismatch results to the user and guides them to the next step.

[0303] Step 6:

[0304] Based on the instructions issued from the terminal, the user performs manual confirmation or resubmission, for example, in case of inconsistency. The input is the display information of the terminal, and the output is the user's corresponding actions. The user executes actions as required.

[0305] 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.

[0306] The system according to the present invention aims to improve the efficiency of application form processing. In addition to existing technologies such as an image input device, an image recognition device, optical character recognition technology, and database collation, by combining an emotion engine, it aims to improve the user experience. This system can not only accurately confirm the seal impression of the application form but also recognize the user's emotional state in real time and adjust the response.

[0307] First, the user acquires the seal impression of the application form as an image and transmits it to the server via the terminal. Inside the server, the image recognition device identifies the type of the seal impression, and the optical character recognition technology converts the character information into text data. This information is stored in the database and centrally managed as seal impression data for each company.

[0308] When a new application form is accepted, the terminal transmits the application data to the server. At the same time, the user's voice and facial expression data are analyzed by the emotion engine. The server executes a process of comparing the past seal impression data and the new data in the database to determine whether there is a match. Furthermore, the user's emotional state analyzed by the emotion engine is used to customize the response. For example, when the user shows emotions such as discomfort or confusion, the terminal immediately provides operation guidance or additional support.

[0309] For example, when a company submits an application, if the user experiences stress, the system detects the user's emotions and displays simpler, easier-to-understand guides in the interface. Furthermore, while the signature verification process is underway, the emotion engine continuously monitors the user's emotional state and dynamically takes action to reduce unnecessary stress.

[0310] Thus, the present invention provides a system that improves both operational efficiency and user experience by streamlining the conventional stamping confirmation process while simultaneously enabling flexible responses tailored to the user's emotional state.

[0311] The following describes the processing flow.

[0312] Step 1:

[0313] The user obtains the application form as image data using a scanner or camera. The obtained image is then saved to the device.

[0314] Step 2:

[0315] The device sends images acquired by the user to the server. During transmission, audio and facial expression data are also collected simultaneously for emotion analysis.

[0316] Step 3:

[0317] The server processes the received stamped image using an image recognition device to identify the type of stamp. It also uses optical character recognition technology to convert the character information within the stamped image into text data.

[0318] Step 4:

[0319] The server stores the identified type of seal and extracted character information in a database and updates the seal data for each company.

[0320] Step 5:

[0321] The device inputs simultaneously transmitted audio and facial expression data into an emotion engine to analyze the user's emotions. This analysis identifies the user's current emotional state.

[0322] Step 6:

[0323] The server compares the new application data with the stamp data stored in the database. If a match is found, the application is automatically approved. If there is a mismatch, a more detailed re-verification will be required.

[0324] Step 7:

[0325] Based on the analysis results of the emotion engine, the device flexibly changes its response if the user is experiencing stress, and displays operation guides and support messages on the screen.

[0326] Step 8:

[0327] Users can receive approval results through their terminal and, if necessary, take additional actions by following the guidance provided by the system.

[0328] This series of steps allows the system to efficiently verify signatures while also supporting user emotions and providing an excellent user experience.

[0329] (Example 2)

[0330] 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".

[0331] Conventional application processing systems often involved manual verification of signatures, leading to inefficient processing and frequent human errors. Furthermore, a lack of consideration for user feelings sometimes resulted in confusion and dissatisfaction. Additionally, achieving highly accurate database management of application forms proved difficult.

[0332] 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.

[0333] In this invention, the server includes means for acquiring electronic images, means for recognizing the type of seal impression, means for storing and comparing information in a database, and means for analyzing the user's emotions and adjusting the interface. This enables rapid and accurate processing of application forms and flexible responses to the user's emotions.

[0334] An "image capture device" is a device used to capture objects or documents in electronic format.

[0335] An "electronic image" is image information that is stored and displayed as digital data.

[0336] A "visual recognition device" is a device that detects and identifies specific shapes and features from electronic images.

[0337] "Character recognition technology" is a technology that electronically extracts handwritten or printed character information and recognizes it as text data.

[0338] An "information storage device" is a device or system for electronically storing and making accessible large amounts of data.

[0339] A "control device" is a device used to manage and instruct specific processes or functions.

[0340] An "emotion analysis device" is a device that analyzes a user's emotional state based on their voice and facial expression data.

[0341] "User interface display" refers to the screens and their arrangement and design that users use to interact with the system.

[0342] This invention provides a system for streamlining application form processing, which can be implemented by combining elements such as an image capture device, a visual recognition device, character recognition technology, an information accumulating device, and an emotion analysis device. The main components are as follows:

[0343] First, the user fills in information on the application form and uses an image capture device to obtain an electronic image of the entire form, including the seal. The terminal temporarily stores this image on the device and then transmits it to the server via the internet.

[0344] On the server, the type of seal is identified from the received electronic image using a visual recognition device. Image processing libraries such as OpenCV and TensorFlow can be used for this process. Next, optical character recognition technology is used to convert the character information within the image into text data. At this stage, Tesseract OCR or the Google Cloud Vision API can be used.

[0345] Next, the server stores the identified type of seal and extracted character information in the information aggregation device. Database systems such as MySQL and MongoDB can be used. Furthermore, the server compares the contents of the application form with existing data in the information aggregation device to determine if they match. Using SQL queries at this stage allows for efficient matching.

[0346] The device collects user voice and facial expression data using an emotion analysis device while the user is operating the system. This can utilize Microsoft Azure's Emotion API, among others. Based on this data, the user's emotions are analyzed, and the interface display is adjusted as needed.

[0347] As a concrete example, when a user submits an application form, if they have any questions about the procedure, the device will provide appropriate support information based on the sentiment analysis results. This allows the user to proceed with the procedure smoothly without feeling stressed.

[0348] An example of a prompt message might be, "Display support information to optimize the user interface based on the user's emotional state."

[0349] In this way, the present invention automates the application form processing process and responds to user emotions, thereby simultaneously achieving operational efficiency and improved user experience.

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

[0351] Step 1:

[0352] The user takes a picture of the application form using the image capture device on the terminal. The input to this process is the physical application form, and the output is an electronic image stored on the terminal. This image will be used in subsequent processing steps.

[0353] Step 2:

[0354] The terminal sends the acquired electronic image to the server. At this stage, the input is the electronic image, and the output is the transmission of image data to the server. The terminal uploads the image data to the server using a secure protocol (e.g., HTTPS).

[0355] Step 3:

[0356] The server analyzes the received electronic image using a visual recognition device to identify the type of seal. The input is the electronic image sent from the terminal, and the output is data representing the recognized type of seal. This process utilizes OpenCV and TensorFlow for feature extraction and matching.

[0357] Step 4:

[0358] The server extracts character information from electronic images using optical character recognition (OCR) technology. The input is an electronic image, and the output is text data. This process involves analyzing the character portion within the image and converting it into character codes using technologies such as Tesseract OCR.

[0359] Step 5:

[0360] The server stores the identified stamp type and extracted character information in the information accumulator. The input is the stamp type and text data obtained in the previous step, and the output is the data stored in the information accumulator. The server uses a database management system to centrally store the information.

[0361] Step 6:

[0362] The server compares the contents of the application form with the data stored in the data aggregation device. Input consists of newly registered data and existing data, while output is the result of the comparison. The server uses SQL queries to verify data consistency and analyzes the results.

[0363] Step 7:

[0364] The device analyzes the user's voice and facial expression data in real time using an emotion analysis device. In this process, the device acquires voice and facial expression data as input and obtains the analyzed user's emotional state as output. The Emotion API and other similar tools are used for emotion analysis.

[0365] Step 8:

[0366] The server adjusts the user interface display based on the emotional state obtained by the emotion analysis device. The input is the user's emotional state data, and the output is the adjusted screen display. In particular, if the user is showing discomfort or confusion, the terminal's display content is changed to be more intuitive and easy to understand.

[0367] Through these processing steps, this system not only automates the processing of application forms but also enables flexible responses that take into account the user's feelings.

[0368] (Application Example 2)

[0369] 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."

[0370] While conventional application processing systems are increasingly automated in verifying signatures, they cannot respond to changes in customer emotions in real time, potentially resulting in a diminished user experience. Furthermore, there is a need to improve the quality of customer service, particularly in handling discrepancies in matching results and manual verification. Efficiently managing and updating diverse signature information specific to each company and organization is also crucial.

[0371] 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.

[0372] In this invention, the server includes means for acquiring the seal impression on the application form as a digital image using an image acquisition device, means for identifying the type of seal impression from the digital image using an image analysis device, means for extracting character information using optical character recognition technology, means for using an emotion estimation engine that analyzes the customer's voice and facial expression data, means for storing and comparing the identified information in an information storage system, and means for dynamically providing guidance based on the customer's emotional state. This improves the efficiency of application form processing, enables appropriate responses to customer emotions, and enhances the user experience.

[0373] An "image acquisition device" is a device used to acquire stamps and textual information from application forms and other documents as digital data.

[0374] An "image analysis device" is a device used to identify specific patterns or types from acquired digital images.

[0375] "Optical character recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0376] An "information storage system" is a database system that centrally manages identified stamps and extracted text information, and performs verification and updating as needed.

[0377] An "emotion estimation engine" is software that analyzes customer voice and facial expression data to estimate their emotional state in real time.

[0378] A "control system" is a computer system that compares the contents of an application form with data in the information storage system to determine whether or not they match.

[0379] "A means of dynamically providing guidance" refers to a function that instantly presents the most appropriate actions or support on the interface according to the customer's current emotional state.

[0380] The following describes embodiments for carrying out this invention. The system aims to streamline the processing of application forms and dynamically adjust the interface according to the customer's emotions.

[0381] The server uses an image acquisition device to capture the seal impression on the application form as a digital image. The acquired image is then analyzed by an image analysis device to identify the type of seal impression, and the character information is extracted as text data using optical character recognition technology. This information is stored in a database within the information storage system, and the seal impression information is managed and updated for each company or organization.

[0382] When a customer uses a terminal to submit a new application form, the terminal sends the data to the server. The server uses a matching system to compare the contents of the application form with past information in the database to determine if there is a match.

[0383] Furthermore, the server uses an emotion estimation engine to analyze customer voice and facial expression data in real time to estimate their emotional state. For example, if a customer shows signs of anxiety or stress, the server dynamically provides the terminal with operational guidance and additional support information. This allows customers to proceed with the process appropriately and quickly.

[0384] As a concrete example, in customer service at physical stores, this system allows staff to adjust their responses based on the customer's current emotional state. For instance, by providing a prompt message from the server such as, "We have detected that the customer is dissatisfied. Please suggest an appropriate response," staff can provide more effective service. This improves both the user experience and operational efficiency.

[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 to photograph the stamp on the application form. The digital image acquired by the image acquisition device is sent from the terminal to the server. The input is the digital image of the stamp taken by the user, and the output is the image data transferred to the server.

[0388] Step 2:

[0389] The server uses an image analysis device to analyze the received digital image and identify the type of seal. The identified information is stored in a database. The input is a digital image, and the output is data of the identified type of seal.

[0390] Step 3:

[0391] The server uses optical character recognition (OCR) technology to extract character information from digital images. The extracted character information is stored in a database. The input is a digital image, and the output is character information in text data format.

[0392] Step 4:

[0393] The server uses information stored in the database within the information storage system to compare new application data with past data. The inputs are the new application data and database data, and the output is the comparison result.

[0394] Step 5:

[0395] Voice and facial expression data from the user are collected via the terminal and analyzed by the server's emotion estimation engine. The input is voice and facial expression data, and the output is estimated emotion state data.

[0396] Step 6:

[0397] The server generates and dynamically presents operation guides and appropriate support information to the terminal based on the user's emotional state. The input is estimated emotional state data, and the output is operation guides and support information. This allows the user to receive responses tailored to their emotions.

[0398] Step 7:

[0399] Prompt messages are generated via a generative AI model and provided to the user or device. This allows the user interface to be adjusted in real time. The input is data for the generative AI model, and the output is the prompt message.

[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). An 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 the following. 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 indicated 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] The system according to the present invention is for automating the verification of seals on paper application forms. It performs a series of steps, from digitizing seals using an image input device, to recognition, storage in a database, verification, and display of results. This makes it possible to significantly reduce the amount of manual verification required while ensuring accuracy.

[0417] In system operation, users first acquire image data of the stamped portion of the application form by digitally scanning or photographing it. This image data is transmitted to the server via a terminal. The server processes the received image with an image recognition device to determine the type of stamp and converts the character information within the stamp impression into text data using optical character recognition technology. The converted information is immediately stored in a database and accumulated as stamp data for each company.

[0418] Next, when a new application form is received, the terminal sends a verification request to the server based on the application details. The server compares the newly acquired stamp data with existing data in the database to determine if they match. This result is quickly returned to the terminal, and the user can receive the verification result. If they match, the application form is automatically approved, and the business process proceeds quickly. On the other hand, if they do not match, the user is notified, and reconfirmation or correction is made as necessary.

[0419] For example, consider a scenario where a company submits a contract application for a new service. When the user scans the application and sends it to the server, the server immediately analyzes the type of seal and text information and stores it in a database. The next time the same company submits an additional service application, the terminal retrieves the seal data from the server database and checks for a match with the previous data. If a match is confirmed, the terminal automatically approves the application, and the user experiences the speed and accuracy of the process.

[0420] Thus, the present invention significantly streamlines the process of verifying seals, reducing the risk of errors and shortening working hours.

[0421] The following describes the processing flow.

[0422] Step 1:

[0423] The user obtains a digital image of the stamped portion of the application form using a scanner or camera. The resulting image is saved on the device.

[0424] Step 2:

[0425] The terminal transmits images acquired by the user to the server through the system interface. The transmitted images arrive at the server in digital format.

[0426] Step 3:

[0427] The server first passes the received stamped image to an image recognition device to identify the type of stamp (round, square, etc.). Subsequently, it uses optical character recognition technology to analyze the string of characters within the stamp impression and convert it into text data.

[0428] Step 4:

[0429] The server stores the analyzed seal type and character information in a database. This allows for the accumulation of seal data for each company, preparing for future matching.

[0430] Step 5:

[0431] When a new application form arrives, the terminal sends a verification request to the server based on that information. This prepares the system for a smooth comparison between the data in the database and the new application data.

[0432] Step 6:

[0433] The server meticulously compares the database records with the newly submitted stamp data to determine if they match. If a complete match is confirmed for the type of stamp and the character information, automatic approval is possible.

[0434] Step 7:

[0435] The terminal receives the matching results sent from the server and displays the results to the user. If a match is found, the user receives a notification that approval is complete. If a mismatch occurs, a warning is displayed, and the user is prompted to manually re-verify or correct the information.

[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] The process of verifying seal impressions in paper records has traditionally relied heavily on visual inspection, resulting in a time-consuming process prone to human error. Furthermore, ensuring accuracy in handling seal types and textual information often led to increased workload.

[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 acquiring a seal impression as a digital image from a paper record using a communication device, means for analyzing the characteristics of the seal impression from the digital image using an information processing device, and means for converting character data from the digital image by applying optical character recognition technology. This enables automatic analysis of the seal impression and accurate data conversion.

[0441] A "communication device" is a device used to acquire digital images from paper records and transmit them to a server.

[0442] An "information processing device" is a device used to analyze and identify the characteristics of a seal impression from a digital image.

[0443] "Optical character recognition technology" is a technology that converts character information within digital images into text data.

[0444] A "memory device" is a device for storing the characteristics of the analyzed seal impression and the converted character data.

[0445] A "computer" is a device that compares application details with information stored in memory and outputs the results.

[0446] The "update function" is a function that updates data stored on a storage device for each organization.

[0447] This invention is a system that improves operational efficiency and accuracy by automating the verification of seal impressions on paper application forms. First, the user uses a communication device to digitally scan or photograph the seal portion of the application form to obtain image data. This image data is transmitted from the terminal to the server via a secure communication protocol.

[0448] The server processes the received digital image using an information processing device. This processing is performed using image recognition software and includes a process of extracting the outline of the seal impression and identifying its characteristics. Optical character recognition technology is also applied to convert the character information within the seal impression into text data. This data conversion makes it possible to accurately acquire information from paper media as digital data.

[0449] The converted data is stored in a storage device. This stored data can then be updated with company or individual signature information. When a new application form is received, the terminal requests the server to compare it with existing information. The server uses a computer to compare the information in the database and determines whether there is a match or not.

[0450] To understand this system concretely, let's consider a scenario where a company submits a contract application for a new service. The user scans the application and sends the image data to the server. The server immediately analyzes the image, digitizes the seal data and text information, and stores it. The next time the same company submits an application for an additional service, the terminal retrieves the past seal data from the server's database and performs a comparison. This automates the processing of application forms, dramatically improving operational efficiency.

[0451] An example of a prompt to input into a generating AI model is, "Please tell me how to implement a system that digitizes the stamps on paper application forms, recognizes and verifies them, and automatically approves them." This prompt allows for the efficient acquisition of specific implementation methods and technical approaches.

[0452] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0453] Step 1:

[0454] The user prepares a paper application form and uses a communication device to digitally scan or photograph the stamped portion. This operation results in the input of image data of the application form. This acquired image data is then transmitted to the server via the terminal.

[0455] Step 2:

[0456] The server processes the received image data using an information processing device. Specifically, it first analyzes the outline of the seal impression using image recognition software and identifies its characteristics. An outline detection algorithm is applied to the input image data, and the type of seal impression is obtained as output. This identification is important to ensure the accuracy of the information.

[0457] Step 3:

[0458] The server uses optical character recognition (OCR) technology to convert character information within image data into text data. This process is performed by an OCR engine, and the input is pre-processed image data. The output is digital text of the character information contained in the seal impression. This text data is then used for subsequent database storage.

[0459] Step 4:

[0460] The server stores the analyzed seal characteristics and converted character data in storage. The input to this storage process is text data, and the output is structured information in a database. This information forms the basis for future matching operations.

[0461] Step 5:

[0462] The terminal sends a verification request to the server based on the newly received application form. The input here is the information from the new application form, and the output is an instruction for the server to perform a database verification accordingly.

[0463] Step 6:

[0464] The server retrieves previously matched seal impression data from the current database and compares it with the new data. The input consists of existing information in the database and the new data, and the output is the result of a match or mismatch determination. This comparison is performed using a sophisticated algorithm.

[0465] Step 7:

[0466] The server sends the matching results to the terminal and requests confirmation from the user. If the results match, the output triggers an automated approval process. If there is a mismatch, the user is warned, and a re-evaluation or manual verification process is initiated.

[0467] (Application Example 1)

[0468] 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."

[0469] Traditionally, the process of verifying customer signatures on application forms and loyalty card usage requests at physical stores has been done manually, which is time-consuming, labor-intensive, and prone to human error. This reduces the efficiency and reliability of the process, hindering improvements in customer service quality. There is a need for a system that can solve this problem and perform quick and accurate signature verification on-site.

[0470] 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.

[0471] In this invention, the server includes means for acquiring the stamping of a document as a digital image using an image acquisition device, means for using an image analysis device to identify the type of stamping from the digital image, and means for extracting character information from the digital image using optical information recognition technology. This makes it possible to verify and approve stamping in real time using a smart device in a physical store.

[0472] An "image acquisition device" is a hardware device used to acquire the stamped portion of a document as a digital image.

[0473] An "image analysis device" is a device that performs image processing to identify the type of seal impression from acquired digital images.

[0474] "Optical information recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0475] An "information recording device" is a device that includes a database for recording the type of stamped item identified and the extracted character information.

[0476] A "computational device" is a system that includes a processor for comparing the contents of a document with data in an information recording device.

[0477] A "smart device" is a portable electronic device used to verify stamping in real time at physical stores.

[0478] This invention is a system for streamlining the verification of stamps on paper application forms and point card usage applications at physical stores. When a customer submits an application form, store staff use a smart device to acquire the stamped portion as a digital image. Specifically, the stamp is scanned using an image acquisition device (smartphone camera). The server receives this image and identifies the type of stamp using an image analysis device (using OpenCV). Furthermore, optical information recognition technology (using OCR software such as Tesseract) is used to extract the character information contained within the stamp.

[0479] This information is stored in an information recording device. The server also uses a computing device to compare the stamped data on the new application form with existing data in the database to determine if they match. If the matching results are correct, the application form is immediately approved, and the confirmation result is displayed to the user on their smart device. If there is a mismatch, a notification is sent to the smart device, prompting the user to perform additional verification.

[0480] As a concrete example, when a new member registers at a restaurant, the customer submits an application form, and a staff member scans the signature using a smart device. The data is immediately processed on the server, allowing the process to proceed quickly. This system enables quick and efficient on-site signature verification, contributing to improved customer service quality.

[0481] As an example of a prompt for the generating AI model, enter the following: "Please scan the stamped portion of the application form below and check if it matches the database. The procedure is to activate the camera, recognize the captured image data, extract the text information, and send it to the server for verification. Please let me know the result."

[0482] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0483] Step 1:

[0484] The user submits an application form at the store, and the terminal (smartphone) uses its camera to scan the stamped portion of the application form. The input is a stamp on paper, and the output is a digital image file. The terminal prepares to send the digital image to the server.

[0485] Step 2:

[0486] The server passes the digital image received from the terminal to image analysis software (OpenCV). The input is digital image data, and the output is the type of stamp identified. The server analyzes the stamps in the image and identifies their type.

[0487] Step 3:

[0488] The server extracts character information from the identified stamp data using OCR software (Tesseract). The input is image data of the stamp. The output is character information in text format. The server registers the acquired character information in a database.

[0489] Step 4:

[0490] The server compares existing stamp data in the database with newly acquired data. The input consists of character information on the server and existing information in the database. The output is the match or mismatch result. The server compares the data and generates the result.

[0491] Step 5:

[0492] The server sends the matching results to the terminal. The input is the matching result data, and the output is the result display on the user's terminal screen. The terminal displays the match / mismatch results to the user and guides them to the next step.

[0493] Step 6:

[0494] Based on instructions issued by the device, the user performs actions such as manual verification or resubmission in case of discrepancies. Input is the information displayed on the device, and output is the user's response. The user takes the necessary actions.

[0495] 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.

[0496] The system according to the present invention aims to improve the efficiency of application form processing. In addition to existing technologies such as image input devices, image recognition devices, optical character recognition technology, and database matching, it combines an emotion engine to enhance the user experience. This system can accurately verify the seal impression on application forms and recognize the user's emotional state in real time, adjusting its response accordingly.

[0497] First, the user obtains an image of the seal impression on the application form and sends it to the server via their terminal. On the server, an image recognition device identifies the type of seal impression, and optical character recognition technology converts the character information into text data. This information is stored in a database and centrally managed as seal impression data for each company.

[0498] When a new application is received, the terminal sends the application data to the server. Simultaneously, the user's voice and facial expression data are analyzed by the emotion engine. The server then compares the new data with past stamp data in the database to determine if there is a match. Furthermore, the user's emotional state, as analyzed by the emotion engine, is used to customize the response. For example, if the user indicates feelings of discomfort or confusion, the terminal immediately provides operational guidance or additional support.

[0499] For example, when a company submits an application, if the user experiences stress, the system detects the user's emotions and displays simpler, easier-to-understand guides in the interface. Furthermore, while the signature verification process is underway, the emotion engine continuously monitors the user's emotional state and dynamically takes action to reduce unnecessary stress.

[0500] Thus, the present invention provides a system that improves both operational efficiency and user experience by streamlining the conventional stamping confirmation process while simultaneously enabling flexible responses tailored to the user's emotional state.

[0501] The following describes the processing flow.

[0502] Step 1:

[0503] The user obtains the application form as image data using a scanner or camera. The obtained image is then saved to the device.

[0504] Step 2:

[0505] The device sends images acquired by the user to the server. During transmission, audio and facial expression data are also collected simultaneously for emotion analysis.

[0506] Step 3:

[0507] The server processes the received stamped image using an image recognition device to identify the type of stamp. It also uses optical character recognition technology to convert the character information within the stamped image into text data.

[0508] Step 4:

[0509] The server stores the identified type of seal and extracted character information in a database and updates the seal data for each company.

[0510] Step 5:

[0511] The device inputs simultaneously transmitted audio and facial expression data into an emotion engine to analyze the user's emotions. This analysis identifies the user's current emotional state.

[0512] Step 6:

[0513] The server compares the new application data with the stamp data stored in the database. If a match is found, the application is automatically approved. If there is a mismatch, a more detailed re-verification will be required.

[0514] Step 7:

[0515] Based on the analysis results of the emotion engine, the device flexibly changes its response if the user is experiencing stress, and displays operation guides and support messages on the screen.

[0516] Step 8:

[0517] Users can receive approval results through their terminal and, if necessary, take additional actions by following the guidance provided by the system.

[0518] This series of steps allows the system to efficiently verify signatures while also supporting user emotions and providing an excellent user experience.

[0519] (Example 2)

[0520] 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."

[0521] Conventional application processing systems often involved manual verification of signatures, leading to inefficient processing and frequent human errors. Furthermore, a lack of consideration for user feelings sometimes resulted in confusion and dissatisfaction. Additionally, achieving highly accurate database management of application forms proved difficult.

[0522] 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.

[0523] In this invention, the server includes means for acquiring electronic images, means for recognizing the type of seal impression, means for storing and comparing information in a database, and means for analyzing the user's emotions and adjusting the interface. This enables rapid and accurate processing of application forms and flexible responses to the user's emotions.

[0524] An "image capture device" is a device used to capture objects or documents in electronic format.

[0525] An "electronic image" is image information that is stored and displayed as digital data.

[0526] A "visual recognition device" is a device that detects and identifies specific shapes and features from electronic images.

[0527] "Character recognition technology" is a technology that electronically extracts handwritten or printed character information and recognizes it as text data.

[0528] An "information storage device" is a device or system for electronically storing and making accessible large amounts of data.

[0529] A "control device" is a device used to manage and instruct specific processes or functions.

[0530] An "emotion analysis device" is a device that analyzes a user's emotional state based on their voice and facial expression data.

[0531] "User interface display" refers to the screens and their arrangement and design that users use to interact with the system.

[0532] This invention provides a system for streamlining application form processing, which can be implemented by combining elements such as an image capture device, a visual recognition device, character recognition technology, an information accumulating device, and an emotion analysis device. The main components are as follows:

[0533] First, the user fills in information on the application form and uses an image capture device to obtain an electronic image of the entire form, including the seal. The terminal temporarily stores this image on the device and then transmits it to the server via the internet.

[0534] On the server, the type of seal is identified from the received electronic image using a visual recognition device. Image processing libraries such as OpenCV and TensorFlow can be used for this process. Next, optical character recognition technology is used to convert the character information within the image into text data. At this stage, Tesseract OCR or the Google Cloud Vision API can be used.

[0535] Next, the server stores the identified type of seal and extracted character information in the information aggregation device. Database systems such as MySQL and MongoDB can be used. Furthermore, the server compares the contents of the application form with existing data in the information aggregation device to determine if they match. Using SQL queries at this stage allows for efficient matching.

[0536] The device collects user voice and facial expression data using an emotion analysis device while the user is operating the system. This can utilize Microsoft Azure's Emotion API, among others. Based on this data, the user's emotions are analyzed, and the interface display is adjusted as needed.

[0537] As a concrete example, when a user submits an application form, if they have any questions about the procedure, the device will provide appropriate support information based on the sentiment analysis results. This allows the user to proceed with the procedure smoothly without feeling stressed.

[0538] An example of a prompt message might be, "Display support information to optimize the user interface based on the user's emotional state."

[0539] In this way, the present invention automates the application form processing process and responds to user emotions, thereby simultaneously achieving operational efficiency and improved user experience.

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

[0541] Step 1:

[0542] The user takes a picture of the application form using the image capture device on the terminal. The input to this process is the physical application form, and the output is an electronic image stored on the terminal. This image will be used in subsequent processing steps.

[0543] Step 2:

[0544] The terminal sends the acquired electronic image to the server. At this stage, the input is the electronic image, and the output is the transmission of image data to the server. The terminal uploads the image data to the server using a secure protocol (e.g., HTTPS).

[0545] Step 3:

[0546] The server analyzes the received electronic image using a visual recognition device to identify the type of seal. The input is the electronic image sent from the terminal, and the output is data representing the recognized type of seal. This process utilizes OpenCV and TensorFlow for feature extraction and matching.

[0547] Step 4:

[0548] The server extracts character information from electronic images using optical character recognition (OCR) technology. The input is an electronic image, and the output is text data. This process involves analyzing the character portion within the image and converting it into character codes using technologies such as Tesseract OCR.

[0549] Step 5:

[0550] The server stores the identified stamp type and extracted character information in the information accumulator. The input is the stamp type and text data obtained in the previous step, and the output is the data stored in the information accumulator. The server uses a database management system to centrally store the information.

[0551] Step 6:

[0552] The server compares the contents of the application form with the data stored in the data aggregation device. Input consists of newly registered data and existing data, while output is the result of the comparison. The server uses SQL queries to verify data consistency and analyzes the results.

[0553] Step 7:

[0554] The device analyzes the user's voice and facial expression data in real time using an emotion analysis device. In this process, the device acquires voice and facial expression data as input and obtains the analyzed user's emotional state as output. The Emotion API and other similar tools are used for emotion analysis.

[0555] Step 8:

[0556] The server adjusts the user interface display based on the emotional state obtained by the emotion analysis device. The input is the user's emotional state data, and the output is the adjusted screen display. In particular, if the user is showing discomfort or confusion, the terminal's display content is changed to be more intuitive and easy to understand.

[0557] Through these processing steps, this system not only automates the processing of application forms but also enables flexible responses that take into account the user's feelings.

[0558] (Application Example 2)

[0559] 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."

[0560] While conventional application processing systems are increasingly automated in verifying signatures, they cannot respond to changes in customer emotions in real time, potentially resulting in a diminished user experience. Furthermore, there is a need to improve the quality of customer service, particularly in handling discrepancies in matching results and manual verification. Efficiently managing and updating diverse signature information specific to each company and organization is also crucial.

[0561] 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.

[0562] In this invention, the server includes means for acquiring the seal impression on the application form as a digital image using an image acquisition device, means for identifying the type of seal impression from the digital image using an image analysis device, means for extracting character information using optical character recognition technology, means for using an emotion estimation engine that analyzes the customer's voice and facial expression data, means for storing and comparing the identified information in an information storage system, and means for dynamically providing guidance based on the customer's emotional state. This improves the efficiency of application form processing, enables appropriate responses to customer emotions, and enhances the user experience.

[0563] An "image acquisition device" is a device used to acquire stamps and textual information from application forms and other documents as digital data.

[0564] An "image analysis device" is a device used to identify specific patterns or types from acquired digital images.

[0565] "Optical character recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0566] An "information storage system" is a database system that centrally manages identified stamps and extracted text information, and performs verification and updating as needed.

[0567] An "emotion estimation engine" is software that analyzes customer voice and facial expression data to estimate their emotional state in real time.

[0568] A "control system" is a computer system that compares the contents of an application form with data in the information storage system to determine whether or not they match.

[0569] "A means of dynamically providing guidance" refers to a function that instantly presents the most appropriate actions or support on the interface according to the customer's current emotional state.

[0570] The following describes embodiments for carrying out this invention. The system aims to streamline the processing of application forms and dynamically adjust the interface according to the customer's emotions.

[0571] The server uses an image acquisition device to capture the seal impression on the application form as a digital image. The acquired image is then analyzed by an image analysis device to identify the type of seal impression, and the character information is extracted as text data using optical character recognition technology. This information is stored in a database within the information storage system, and the seal impression information is managed and updated for each company or organization.

[0572] When a customer uses a terminal to submit a new application form, the terminal sends the data to the server. The server uses a matching system to compare the contents of the application form with past information in the database to determine if there is a match.

[0573] Furthermore, the server uses an emotion estimation engine to analyze customer voice and facial expression data in real time to estimate their emotional state. For example, if a customer shows signs of anxiety or stress, the server dynamically provides the terminal with operational guidance and additional support information. This allows customers to proceed with the process appropriately and quickly.

[0574] As a concrete example, in customer service at physical stores, this system allows staff to adjust their responses based on the customer's current emotional state. For instance, by providing a prompt message from the server such as, "We have detected that the customer is dissatisfied. Please suggest an appropriate response," staff can provide more effective service. This improves both the user experience and operational efficiency.

[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 to photograph the stamp on the application form. The digital image acquired by the image acquisition device is sent from the terminal to the server. The input is the digital image of the stamp taken by the user, and the output is the image data transferred to the server.

[0578] Step 2:

[0579] The server uses an image analysis device to analyze the received digital image and identify the type of seal. The identified information is stored in a database. The input is a digital image, and the output is data of the identified type of seal.

[0580] Step 3:

[0581] The server uses optical character recognition (OCR) technology to extract character information from digital images. The extracted character information is stored in a database. The input is a digital image, and the output is character information in text data format.

[0582] Step 4:

[0583] The server uses information stored in the database within the information storage system to compare new application data with past data. The inputs are the new application data and database data, and the output is the comparison result.

[0584] Step 5:

[0585] Voice and facial expression data from the user are collected via the terminal and analyzed by the server's emotion estimation engine. The input is voice and facial expression data, and the output is estimated emotion state data.

[0586] Step 6:

[0587] The server generates and dynamically presents operation guides and appropriate support information to the terminal based on the user's emotional state. The input is estimated emotional state data, and the output is operation guides and support information. This allows the user to receive responses tailored to their emotions.

[0588] Step 7:

[0589] Prompt messages are generated via a generative AI model and provided to the user or device. This allows the user interface to be adjusted in real time. The input is data for the generative AI model, and the output is the prompt message.

[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). An 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 the following. 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 indicated 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] The system according to the present invention is for automating the verification of seals on paper application forms. It performs a series of steps, from digitizing seals using an image input device, to recognition, storage in a database, verification, and display of results. This makes it possible to significantly reduce the amount of manual verification required while ensuring accuracy.

[0608] In system operation, users first acquire image data of the stamped portion of the application form by digitally scanning or photographing it. This image data is transmitted to the server via a terminal. The server processes the received image with an image recognition device to determine the type of stamp and converts the character information within the stamp impression into text data using optical character recognition technology. The converted information is immediately stored in a database and accumulated as stamp data for each company.

[0609] Next, when a new application form is received, the terminal sends a verification request to the server based on the application details. The server compares the newly acquired stamp data with existing data in the database to determine if they match. This result is quickly returned to the terminal, and the user can receive the verification result. If they match, the application form is automatically approved, and the business process proceeds quickly. On the other hand, if they do not match, the user is notified, and reconfirmation or correction is made as necessary.

[0610] For example, consider a scenario where a company submits a contract application for a new service. When the user scans the application and sends it to the server, the server immediately analyzes the type of seal and text information and stores it in a database. The next time the same company submits an additional service application, the terminal retrieves the seal data from the server database and checks for a match with the previous data. If a match is confirmed, the terminal automatically approves the application, and the user experiences the speed and accuracy of the process.

[0611] Thus, the present invention significantly streamlines the process of verifying seals, reducing the risk of errors and shortening working hours.

[0612] The following describes the processing flow.

[0613] Step 1:

[0614] The user obtains a digital image of the stamped portion of the application form using a scanner or camera. The resulting image is saved on the device.

[0615] Step 2:

[0616] The terminal transmits images acquired by the user to the server through the system interface. The transmitted images arrive at the server in digital format.

[0617] Step 3:

[0618] The server first passes the received stamped image to an image recognition device to identify the type of stamp (round, square, etc.). Subsequently, it uses optical character recognition technology to analyze the string of characters within the stamp impression and convert it into text data.

[0619] Step 4:

[0620] The server stores the analyzed seal type and character information in a database. This allows for the accumulation of seal data for each company, preparing for future matching.

[0621] Step 5:

[0622] When a new application form arrives, the terminal sends a verification request to the server based on that information. This prepares the system for a smooth comparison between the data in the database and the new application data.

[0623] Step 6:

[0624] The server meticulously compares the database records with the newly submitted stamp data to determine if they match. If a complete match is confirmed for the type of stamp and the character information, automatic approval is possible.

[0625] Step 7:

[0626] The terminal receives the matching results sent from the server and displays the results to the user. If a match is found, the user receives a notification that approval is complete. If a mismatch occurs, a warning is displayed, and the user is prompted to manually re-verify or correct the information.

[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] The process of verifying seal impressions in paper records has traditionally relied heavily on visual inspection, resulting in a time-consuming process prone to human error. Furthermore, ensuring accuracy in handling seal types and textual information often led to increased workload.

[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 acquiring a seal impression as a digital image from a paper record using a communication device, means for analyzing the characteristics of the seal impression from the digital image using an information processing device, and means for converting character data from the digital image by applying optical character recognition technology. This enables automatic analysis of the seal impression and accurate data conversion.

[0632] A "communication device" is a device used to acquire digital images from paper records and transmit them to a server.

[0633] An "information processing device" is a device used to analyze and identify the characteristics of a seal impression from a digital image.

[0634] "Optical character recognition technology" is a technology that converts character information within digital images into text data.

[0635] A "memory device" is a device for storing the characteristics of the analyzed seal impression and the converted character data.

[0636] A "computer" is a device that compares application details with information stored in memory and outputs the results.

[0637] The "update function" is a function that updates data stored on a storage device for each organization.

[0638] This invention is a system that improves operational efficiency and accuracy by automating the verification of seal impressions on paper application forms. First, the user uses a communication device to digitally scan or photograph the seal portion of the application form to obtain image data. This image data is transmitted from the terminal to the server via a secure communication protocol.

[0639] The server processes the received digital image using an information processing device. This processing is performed using image recognition software and includes a process of extracting the outline of the seal impression and identifying its characteristics. Optical character recognition technology is also applied to convert the character information within the seal impression into text data. This data conversion makes it possible to accurately acquire information from paper media as digital data.

[0640] The converted data is stored in a storage device. This stored data can then be updated with company or individual signature information. When a new application form is received, the terminal requests the server to compare it with existing information. The server uses a computer to compare the information in the database and determines whether there is a match or not.

[0641] To understand this system concretely, let's consider a scenario where a company submits a contract application for a new service. The user scans the application and sends the image data to the server. The server immediately analyzes the image, digitizes the seal data and text information, and stores it. The next time the same company submits an application for an additional service, the terminal retrieves the past seal data from the server's database and performs a comparison. This automates the processing of application forms, dramatically improving operational efficiency.

[0642] An example of a prompt to input into a generating AI model is, "Please tell me how to implement a system that digitizes the stamps on paper application forms, recognizes and verifies them, and automatically approves them." This prompt allows for the efficient acquisition of specific implementation methods and technical approaches.

[0643] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0644] Step 1:

[0645] The user prepares a paper application form and uses a communication device to digitally scan or photograph the stamped portion. This operation results in the input of image data of the application form. This acquired image data is then transmitted to the server via the terminal.

[0646] Step 2:

[0647] The server processes the received image data using an information processing device. Specifically, it first analyzes the outline of the seal impression using image recognition software and identifies its characteristics. An outline detection algorithm is applied to the input image data, and the type of seal impression is obtained as output. This identification is important to ensure the accuracy of the information.

[0648] Step 3:

[0649] The server uses optical character recognition (OCR) technology to convert character information within image data into text data. This process is performed by an OCR engine, and the input is pre-processed image data. The output is digital text of the character information contained in the seal impression. This text data is then used for subsequent database storage.

[0650] Step 4:

[0651] The server stores the analyzed seal characteristics and converted character data in storage. The input to this storage process is text data, and the output is structured information in a database. This information forms the basis for future matching operations.

[0652] Step 5:

[0653] The terminal sends a verification request to the server based on the newly received application form. The input here is the information from the new application form, and the output is an instruction for the server to perform a database verification accordingly.

[0654] Step 6:

[0655] The server retrieves previously matched seal impression data from the current database and compares it with the new data. The input consists of existing information in the database and the new data, and the output is the result of a match or mismatch determination. This comparison is performed using a sophisticated algorithm.

[0656] Step 7:

[0657] The server sends the matching results to the terminal and requests confirmation from the user. If the results match, the output triggers an automated approval process. If there is a mismatch, the user is warned, and a re-evaluation or manual verification process is initiated.

[0658] (Application Example 1)

[0659] 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".

[0660] Traditionally, the process of verifying customer signatures on application forms and loyalty card usage requests at physical stores has been done manually, which is time-consuming, labor-intensive, and prone to human error. This reduces the efficiency and reliability of the process, hindering improvements in customer service quality. There is a need for a system that can solve this problem and perform quick and accurate signature verification on-site.

[0661] 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.

[0662] In this invention, the server includes means for acquiring the stamping of a document as a digital image using an image acquisition device, means for using an image analysis device to identify the type of stamping from the digital image, and means for extracting character information from the digital image using optical information recognition technology. This makes it possible to verify and approve stamping in real time using a smart device in a physical store.

[0663] An "image acquisition device" is a hardware device used to acquire the stamped portion of a document as a digital image.

[0664] An "image analysis device" is a device that performs image processing to identify the type of seal impression from acquired digital images.

[0665] "Optical information recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0666] An "information recording device" is a device that includes a database for recording the type of stamped item identified and the extracted character information.

[0667] A "computational device" is a system that includes a processor for comparing the contents of a document with data in an information recording device.

[0668] A "smart device" is a portable electronic device used to verify stamping in real time at physical stores.

[0669] This invention is a system for streamlining the verification of stamps on paper application forms and point card usage applications at physical stores. When a customer submits an application form, store staff use a smart device to acquire the stamped portion as a digital image. Specifically, the stamp is scanned using an image acquisition device (smartphone camera). The server receives this image and identifies the type of stamp using an image analysis device (using OpenCV). Furthermore, optical information recognition technology (using OCR software such as Tesseract) is used to extract the character information contained within the stamp.

[0670] This information is stored in an information recording device. The server also uses a computing device to compare the stamped data on the new application form with existing data in the database to determine if they match. If the matching results are correct, the application form is immediately approved, and the confirmation result is displayed to the user on their smart device. If there is a mismatch, a notification is sent to the smart device, prompting the user to perform additional verification.

[0671] As a concrete example, when a new member registers at a restaurant, the customer submits an application form, and a staff member scans the signature using a smart device. The data is immediately processed on the server, allowing the process to proceed quickly. This system enables quick and efficient on-site signature verification, contributing to improved customer service quality.

[0672] As an example of a prompt for the generating AI model, enter the following: "Please scan the stamped portion of the application form below and check if it matches the database. The procedure is to activate the camera, recognize the captured image data, extract the text information, and send it to the server for verification. Please let me know the result."

[0673] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0674] Step 1:

[0675] The user submits an application form at the store, and the terminal (smartphone) uses its camera to scan the stamped portion of the application form. The input is a stamp on paper, and the output is a digital image file. The terminal prepares to send the digital image to the server.

[0676] Step 2:

[0677] The server passes the digital image received from the terminal to image analysis software (OpenCV). The input is digital image data, and the output is the type of stamp identified. The server analyzes the stamps in the image and identifies their type.

[0678] Step 3:

[0679] The server extracts character information from the identified stamp data using OCR software (Tesseract). The input is image data of the stamp. The output is character information in text format. The server registers the acquired character information in a database.

[0680] Step 4:

[0681] The server compares existing stamp data in the database with newly acquired data. The input consists of character information on the server and existing information in the database. The output is the match or mismatch result. The server compares the data and generates the result.

[0682] Step 5:

[0683] The server sends the matching results to the terminal. The input is the matching result data, and the output is the result display on the user's terminal screen. The terminal displays the match / mismatch results to the user and guides them to the next step.

[0684] Step 6:

[0685] Based on instructions issued by the device, the user performs actions such as manual verification or resubmission in case of discrepancies. Input is the information displayed on the device, and output is the user's response. The user takes the necessary actions.

[0686] 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.

[0687] The system according to the present invention aims to improve the efficiency of application form processing. In addition to existing technologies such as image input devices, image recognition devices, optical character recognition technology, and database matching, it combines an emotion engine to enhance the user experience. This system can accurately verify the seal impression on application forms and recognize the user's emotional state in real time, adjusting its response accordingly.

[0688] First, the user obtains an image of the seal impression on the application form and sends it to the server via their terminal. On the server, an image recognition device identifies the type of seal impression, and optical character recognition technology converts the character information into text data. This information is stored in a database and centrally managed as seal impression data for each company.

[0689] When a new application is received, the terminal sends the application data to the server. Simultaneously, the user's voice and facial expression data are analyzed by the emotion engine. The server then compares the new data with past stamp data in the database to determine if there is a match. Furthermore, the user's emotional state, as analyzed by the emotion engine, is used to customize the response. For example, if the user indicates feelings of discomfort or confusion, the terminal immediately provides operational guidance or additional support.

[0690] For example, when a company submits an application, if the user experiences stress, the system detects the user's emotions and displays simpler, easier-to-understand guides in the interface. Furthermore, while the signature verification process is underway, the emotion engine continuously monitors the user's emotional state and dynamically takes action to reduce unnecessary stress.

[0691] Thus, the present invention provides a system that improves both operational efficiency and user experience by streamlining the conventional stamping confirmation process while simultaneously enabling flexible responses tailored to the user's emotional state.

[0692] The following describes the processing flow.

[0693] Step 1:

[0694] The user obtains the application form as image data using a scanner or camera. The obtained image is then saved to the device.

[0695] Step 2:

[0696] The device sends images acquired by the user to the server. During transmission, audio and facial expression data are also collected simultaneously for emotion analysis.

[0697] Step 3:

[0698] The server processes the received stamped image using an image recognition device to identify the type of stamp. It also uses optical character recognition technology to convert the character information within the stamped image into text data.

[0699] Step 4:

[0700] The server stores the identified type of seal and extracted character information in a database and updates the seal data for each company.

[0701] Step 5:

[0702] The device inputs simultaneously transmitted audio and facial expression data into an emotion engine to analyze the user's emotions. This analysis identifies the user's current emotional state.

[0703] Step 6:

[0704] The server compares the new application data with the stamp data stored in the database. If a match is found, the application is automatically approved. If there is a mismatch, a more detailed re-verification will be required.

[0705] Step 7:

[0706] Based on the analysis results of the emotion engine, the device flexibly changes its response if the user is experiencing stress, and displays operation guides and support messages on the screen.

[0707] Step 8:

[0708] Users can receive approval results through their terminal and, if necessary, take additional actions by following the guidance provided by the system.

[0709] This series of steps allows the system to efficiently verify signatures while also supporting user emotions and providing an excellent user experience.

[0710] (Example 2)

[0711] 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".

[0712] Conventional application processing systems often involved manual verification of signatures, leading to inefficient processing and frequent human errors. Furthermore, a lack of consideration for user feelings sometimes resulted in confusion and dissatisfaction. Additionally, achieving highly accurate database management of application forms proved difficult.

[0713] 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.

[0714] In this invention, the server includes means for acquiring electronic images, means for recognizing the type of seal impression, means for storing and comparing information in a database, and means for analyzing the user's emotions and adjusting the interface. This enables rapid and accurate processing of application forms and flexible responses to the user's emotions.

[0715] An "image capture device" is a device used to capture objects or documents in electronic format.

[0716] An "electronic image" is image information that is stored and displayed as digital data.

[0717] A "visual recognition device" is a device that detects and identifies specific shapes and features from electronic images.

[0718] "Character recognition technology" is a technology that electronically extracts handwritten or printed character information and recognizes it as text data.

[0719] An "information storage device" is a device or system for electronically storing and making accessible large amounts of data.

[0720] A "control device" is a device used to manage and instruct specific processes or functions.

[0721] An "emotion analysis device" is a device that analyzes a user's emotional state based on their voice and facial expression data.

[0722] "User interface display" refers to the screens and their arrangement and design that users use to interact with the system.

[0723] This invention provides a system for streamlining application form processing, which can be implemented by combining elements such as an image capture device, a visual recognition device, character recognition technology, an information accumulating device, and an emotion analysis device. The main components are as follows:

[0724] First, the user fills in information on the application form and uses an image capture device to obtain an electronic image of the entire form, including the seal. The terminal temporarily stores this image on the device and then transmits it to the server via the internet.

[0725] On the server, the type of seal is identified from the received electronic image using a visual recognition device. Image processing libraries such as OpenCV and TensorFlow can be used for this process. Next, optical character recognition technology is used to convert the character information within the image into text data. At this stage, Tesseract OCR or the Google Cloud Vision API can be used.

[0726] Next, the server stores the identified type of seal and extracted character information in the information aggregation device. Database systems such as MySQL and MongoDB can be used. Furthermore, the server compares the contents of the application form with existing data in the information aggregation device to determine if they match. Using SQL queries at this stage allows for efficient matching.

[0727] The device collects user voice and facial expression data using an emotion analysis device while the user is operating the system. This can utilize Microsoft Azure's Emotion API, among others. Based on this data, the user's emotions are analyzed, and the interface display is adjusted as needed.

[0728] As a concrete example, when a user submits an application form, if they have any questions about the procedure, the device will provide appropriate support information based on the sentiment analysis results. This allows the user to proceed with the procedure smoothly without feeling stressed.

[0729] An example of a prompt message might be, "Display support information to optimize the user interface based on the user's emotional state."

[0730] In this way, the present invention automates the application form processing process and responds to user emotions, thereby simultaneously achieving operational efficiency and improved user experience.

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

[0732] Step 1:

[0733] The user takes a picture of the application form using the image capture device on the terminal. The input to this process is the physical application form, and the output is an electronic image stored on the terminal. This image will be used in subsequent processing steps.

[0734] Step 2:

[0735] The terminal sends the acquired electronic image to the server. At this stage, the input is the electronic image, and the output is the transmission of image data to the server. The terminal uploads the image data to the server using a secure protocol (e.g., HTTPS).

[0736] Step 3:

[0737] The server analyzes the received electronic image using a visual recognition device to identify the type of seal. The input is the electronic image sent from the terminal, and the output is data representing the recognized type of seal. This process utilizes OpenCV and TensorFlow for feature extraction and matching.

[0738] Step 4:

[0739] The server extracts character information from electronic images using optical character recognition (OCR) technology. The input is an electronic image, and the output is text data. This process involves analyzing the character portion within the image and converting it into character codes using technologies such as Tesseract OCR.

[0740] Step 5:

[0741] The server stores the identified stamp type and extracted character information in the information accumulator. The input is the stamp type and text data obtained in the previous step, and the output is the data stored in the information accumulator. The server uses a database management system to centrally store the information.

[0742] Step 6:

[0743] The server compares the contents of the application form with the data stored in the data aggregation device. Input consists of newly registered data and existing data, while output is the result of the comparison. The server uses SQL queries to verify data consistency and analyzes the results.

[0744] Step 7:

[0745] The device analyzes the user's voice and facial expression data in real time using an emotion analysis device. In this process, the device acquires voice and facial expression data as input and obtains the analyzed user's emotional state as output. The Emotion API and other similar tools are used for emotion analysis.

[0746] Step 8:

[0747] The server adjusts the user interface display based on the emotional state obtained by the emotion analysis device. The input is the user's emotional state data, and the output is the adjusted screen display. In particular, if the user is showing discomfort or confusion, the terminal's display content is changed to be more intuitive and easy to understand.

[0748] Through these processing steps, this system not only automates the processing of application forms but also enables flexible responses that take into account the user's feelings.

[0749] (Application Example 2)

[0750] 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".

[0751] While conventional application processing systems are increasingly automated in verifying signatures, they cannot respond to changes in customer emotions in real time, potentially resulting in a diminished user experience. Furthermore, there is a need to improve the quality of customer service, particularly in handling discrepancies in matching results and manual verification. Efficiently managing and updating diverse signature information specific to each company and organization is also crucial.

[0752] 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.

[0753] In this invention, the server includes means for acquiring the seal impression on the application form as a digital image using an image acquisition device, means for identifying the type of seal impression from the digital image using an image analysis device, means for extracting character information using optical character recognition technology, means for using an emotion estimation engine that analyzes the customer's voice and facial expression data, means for storing and comparing the identified information in an information storage system, and means for dynamically providing guidance based on the customer's emotional state. This improves the efficiency of application form processing, enables appropriate responses to customer emotions, and enhances the user experience.

[0754] An "image acquisition device" is a device used to acquire stamps and textual information from application forms and other documents as digital data.

[0755] An "image analysis device" is a device used to identify specific patterns or types from acquired digital images.

[0756] "Optical character recognition technology" is a technology that analyzes character information from digital images and extracts it as text data.

[0757] An "information storage system" is a database system that centrally manages identified stamps and extracted text information, and performs verification and updating as needed.

[0758] An "emotion estimation engine" is software that analyzes customer voice and facial expression data to estimate their emotional state in real time.

[0759] A "control system" is a computer system that compares the contents of an application form with data in the information storage system to determine whether or not they match.

[0760] "A means of dynamically providing guidance" refers to a function that instantly presents the most appropriate actions or support on the interface according to the customer's current emotional state.

[0761] The following describes embodiments for carrying out this invention. The system aims to streamline the processing of application forms and dynamically adjust the interface according to the customer's emotions.

[0762] The server uses an image acquisition device to capture the seal impression on the application form as a digital image. The acquired image is then analyzed by an image analysis device to identify the type of seal impression, and the character information is extracted as text data using optical character recognition technology. This information is stored in a database within the information storage system, and the seal impression information is managed and updated for each company or organization.

[0763] When a customer uses a terminal to submit a new application form, the terminal sends the data to the server. The server uses a matching system to compare the contents of the application form with past information in the database to determine if there is a match.

[0764] Furthermore, the server uses an emotion estimation engine to analyze customer voice and facial expression data in real time to estimate their emotional state. For example, if a customer shows signs of anxiety or stress, the server dynamically provides the terminal with operational guidance and additional support information. This allows customers to proceed with the process appropriately and quickly.

[0765] As a concrete example, in customer service at physical stores, this system allows staff to adjust their responses based on the customer's current emotional state. For instance, by providing a prompt message from the server such as, "We have detected that the customer is dissatisfied. Please suggest an appropriate response," staff can provide more effective service. This improves both the user experience and operational efficiency.

[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 to photograph the stamp on the application form. The digital image acquired by the image acquisition device is sent from the terminal to the server. The input is the digital image of the stamp taken by the user, and the output is the image data transferred to the server.

[0769] Step 2:

[0770] The server uses an image analysis device to analyze the received digital image and identify the type of seal. The identified information is stored in a database. The input is a digital image, and the output is data of the identified type of seal.

[0771] Step 3:

[0772] The server uses optical character recognition (OCR) technology to extract character information from digital images. The extracted character information is stored in a database. The input is a digital image, and the output is character information in text data format.

[0773] Step 4:

[0774] The server uses information stored in the database within the information storage system to compare new application data with past data. The inputs are the new application data and database data, and the output is the comparison result.

[0775] Step 5:

[0776] Voice and facial expression data from the user are collected via the terminal and analyzed by the server's emotion estimation engine. The input is voice and facial expression data, and the output is estimated emotion state data.

[0777] Step 6:

[0778] The server generates and dynamically presents operation guides and appropriate support information to the terminal based on the user's emotional state. The input is estimated emotional state data, and the output is operation guides and support information. This allows the user to receive responses tailored to their emotions.

[0779] Step 7:

[0780] Prompt messages are generated via a generative AI model and provided to the user or device. This allows the user interface to be adjusted in real time. The input is data for the generative AI model, and the output is the prompt message.

[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). An 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 the following. 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 indicated 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 of acquiring the seal impression on an application form as a digital image using an image input device,

[0805] A means of using an image recognition device that identifies the type of seal impression from the aforementioned digital image,

[0806] A means for extracting character information from the aforementioned digital image using optical character recognition technology,

[0807] Means for storing the identified type of seal and extracted character information in a database,

[0808] A means of using a control device that compares the contents of the application form with the information in the database,

[0809] A means for automatically verifying the seal impression on the application form based on the aforementioned verification results and displaying the results,

[0810] A system that includes this.

[0811] (Claim 2)

[0812] The system according to claim 1, further comprising means for issuing a warning and prompting manual verification if the matching results do not match.

[0813] (Claim 3)

[0814] The system according to claim 1, wherein the database includes an update function for updating seal information for each company.

[0815] "Example 1"

[0816] (Claim 1)

[0817] A means of acquiring a seal impression as a digital image from a paper record using a communication device,

[0818] A means of using an information processing device that analyzes the characteristics of the seal impression from the aforementioned digital image,

[0819] A means for converting character data from the digital image by applying optical character recognition technology,

[0820] A means of using a storage device that stores the characteristics of the analyzed seal impression and the converted character data,

[0821] A means of using a computer to compare the application details with the information in the aforementioned storage device,

[0822] A means to automate the application approval process based on the aforementioned comparison results and output the results,

[0823] A system that includes this.

[0824] (Claim 2)

[0825] The system according to claim 1, further comprising a function to issue a warning and prompt a re-evaluation when the comparison results are inconsistent.

[0826] (Claim 3)

[0827] The system according to claim 1, wherein the storage device has an update function for updating seal impression data for each organization.

[0828] "Application Example 1"

[0829] (Claim 1)

[0830] A means for acquiring a document's seal as a digital image using an image acquisition device,

[0831] A means of using an image analysis device that identifies the type of seal impression from the aforementioned digital image,

[0832] A means for extracting character information from the aforementioned digital image using optical information recognition technology,

[0833] Means for storing the identified type of stamp and extracted character information in an information recording device,

[0834] A means of using a computing device to compare the contents of a document with the information in the aforementioned information recording device,

[0835] A means for automatically verifying the seal on a document based on the aforementioned verification results and displaying the results,

[0836] A means of verifying and approving the aforementioned stamping in real time via a smart device at a physical store,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, further comprising means for issuing a notification and prompting for further verification if the matching results do not match.

[0840] (Claim 3)

[0841] The system according to claim 1, wherein the information recording device includes a correction function for updating stamp information for each organization.

[0842] "Example 2 of combining an emotion engine"

[0843] (Claim 1)

[0844] A means for acquiring the seal impression on an application form as an electronic image using an image acquisition device,

[0845] Means for using a visual recognition device to identify the type of seal impression from the aforementioned electronic image,

[0846] A means for extracting character information from the aforementioned electronic image using character recognition technology,

[0847] Means for storing the identified seal impression type and extracted character information in an information storage device,

[0848] A means of using a control device that compares the contents of the application form with the information in the information accumulating device,

[0849] A means for automatically verifying the seal impression on the application form based on the aforementioned verification results and presenting the results,

[0850] A means of using an emotion analysis device that analyzes the user's voice and video data,

[0851] Means for adjusting the user interface display based on the emotion analysis results,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, further comprising means for issuing a warning and prompting manual verification if the matching results do not match.

[0855] (Claim 3)

[0856] The information accumulating device is equipped with an information update function for updating seal impression information for each organization, according to claim 1.

[0857] "Application example 2 when combining with an emotional engine"

[0858] (Claim 1)

[0859] A means of acquiring the seal impression on an application form as a digital image using an image acquisition device,

[0860] A means of using an image analysis device that identifies the type of seal impression from the aforementioned digital image,

[0861] A means for extracting character information from the aforementioned digital image using optical character recognition technology,

[0862] Means for storing the identified type of seal and extracted character information in an information storage system,

[0863] A means of using a control system that compares the contents of the application form with the information stored in the aforementioned information storage system,

[0864] A means of using an emotion estimation engine that analyzes customer voice and facial expression data,

[0865] A means for dynamically providing operation guides and additional support based on the customer's emotional state obtained by the emotion estimation engine,

[0866] A means for automatically verifying the seal impression on the application form based on the aforementioned verification results and displaying the results,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, further comprising means for issuing a warning and prompting manual verification if the matching results do not match, and means for presenting a response method that takes customer feelings into consideration.

[0870] (Claim 3)

[0871] The information storage system according to claim 1, further comprising a circuit for updating stamp information for each organization. [Explanation of Symbols]

[0872] 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 of acquiring the seal impression on an application form as a digital image using an image input device, A means of using an image recognition device that identifies the type of seal impression from the aforementioned digital image, A means for extracting character information from the aforementioned digital image using optical character recognition technology, Means for storing the identified type of seal and extracted character information in a database, A means of using a control device that compares the contents of the application form with the information in the database, A means for automatically verifying the seal impression on the application form based on the aforementioned verification results and displaying the results, A system that includes this.

2. The system according to claim 1, further comprising means for issuing a warning and prompting manual verification if the matching results do not match.

3. The system according to claim 1, wherein the database includes an update function for updating seal information for each company.

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