Method of controlling registration server and client terminal, registration server, and client terminal

Abstract

To provide a program having a mechanism capable of preventing a AI generation image from being registered when registering a certificate image in a registering system online, and to provide a method for controlling a registering server and client terminals, the registering server, and the client terminals.SOLUTION: When a certification image registering server 501 executes the registering processing of inputted information including an image from communication equipment 102, a AI image identifying part 606 identifies whether or not the image included in the inputted information is a AI generation image, and when it is identified that the image is the AI generation image as the result of the identification, the registering processing is stopped.SELECTED DRAWING: Figure 7

Description

[Technical Field]

[0001] The present invention relates to a program, a registration server and a client terminal control method, a registration server, and a client terminal. [Background technology]

[0002] In recent years, image generation technology using generative AI has become widespread, and individuals can now easily generate images using generative AI. This has made it possible for anyone to easily generate realistic images, but at the same time, there have been occasional cases where malicious users have used generative AI to generate images of fabricated incidents or accidents (hereinafter referred to as AI-generated images), which has become a problem.

[0003] In order to prevent the misuse of such AI-generated images, various countries are rushing to establish laws and development guidelines regarding AI-generated images. For example, by including information on whether an image is AI-generated in its metadata, it is being considered that in the future users will be able to clearly distinguish whether an image is AI-generated or not using that metadata.

[0004] Recently, there have been cases where various images, such as a person's own photo for a matching app or a situational photo showing the damage caused by a traffic accident or disaster, are registered online and used as identification images (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-069307 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the current registration system cannot distinguish whether an image registered as a proof image is a photograph or an AI-generated image, which means that there is a possibility that an AI-generated image may be registered in the registration system as an important proof image.

[0007] In response to the above-mentioned problems, the present invention aims to provide a mechanism that can prevent AI-generated images from being registered when registering proof images in an online registration system. [Means for solving the problem]

[0008] In order to solve the above problem, the program of claim 1 of the present invention is a program for executing a registration process of input information from a client terminal in a registration server, wherein the input information includes image data, and the computer of the registration server functions as a server-side image identification means for identifying whether the image data is an AI-generated image or not, and as a stop means for stopping the registration process when the server-side image identification means identifies the image data as an AI-generated image.

[0009] In order to solve the above problem, the program of claim 6 of the present invention is a program for executing a registration process in a client terminal, which transmits input information from a user to a registration server and registers the input information in the registration server, wherein the input information includes image data, and the program causes the computer of the client terminal to function as a transmission means for transmitting the input information to the registration server, a client-side image identification means for identifying whether the image data is an AI-generated image before the transmission means transmits the input information to the registration server, and a cancellation means for canceling the registration process if the client-side image identification means identifies the image data as an AI-generated image. [Effects of the Invention]

[0010] According to the present invention, when registering a proof image in an online registration system, it is possible to prevent an AI-generated image from being registered.

Brief Description of the Drawings

[0011] [Figure 1] It is a block diagram schematically showing the network configuration of a communication system including an AI image generation server and a communication device as the client terminal of the present invention. [Figure 2] It is a block diagram schematically explaining the hardware configuration of the AI image generation server in FIG. 1. [Figure 3] It is a block diagram schematically explaining the hardware configuration of the communication device in FIG. 1. [Figure 4] It is a flowchart showing the procedure of image generation processing by a generated AI in the communication system of FIG. 1. [Figure 5] It is a block diagram schematically showing the network configuration for proof image registration according to Example 1 including a proof image registration server as the registration server of the present invention and the communication device in FIG. 1. [Figure 6] It is a block diagram schematically explaining the hardware configuration of the proof image registration server in FIG. 5. [Figure 7] It is a flowchart showing the procedure of the proof image registration processing according to Example 1 executed in the proof image registration server. [Figure 8] It is a flowchart showing the procedure of the proof image registration processing according to Example 2 executed in the communication device.

Modes for Carrying Out the Invention

[0012] Hereinafter, modes for carrying out the present invention will be described with reference to the drawings. Note that the following embodiments do not limit the present invention according to the claims, and not all combinations of the features described in the present embodiment are essential for the solution means of the present invention.

[0013] <Regarding AI-generated Images> First, the AI-generated image in this embodiment will be described.

[0014] FIG. 1 is a block diagram that schematically shows the network configuration of a communication system 100 that includes an AI image generation server 101 and a communication device 102 that serves as a client terminal according to this embodiment.

[0015] 1, a communication system 100 is composed of an AI image generation server 101 and a communication device 102. The AI ​​image generation server 101 and the communication device 102 can communicate with each other via a network 104.

[0016] In communication system 100, communication device 102 makes an image generation request in accordance with instructions received from a user. AI image generation server 101 generates an image (hereinafter referred to as an "AI-generated image") using a generation AI in accordance with the generation request received from communication device 102, and transmits the generated AI-generated image to communication device 102.

[0017] The communication device 102 may be any processing terminal that has an application capable of communicating with the AI ​​image generation server 101, such as a general-purpose PC, a smartphone, or a tablet terminal.

[0018] FIG. 2 is a block diagram that schematically illustrates the hardware configuration of the AI ​​image generation server 101.

[0019] 2, the AI ​​image generation server 101 includes a CPU 201, a RAM 202, a ROM 203, a storage unit 204, a GPU 207, an AI-generated identification information addition unit 208, and a network I / F 209. These are connected to each other via a bus 210.

[0020] The CPU 201 controls the operation of the AI ​​image generation server 101 and operates based on a program stored in the RAM 202. The ROM 203 is a boot ROM that stores the system boot program and the like. The storage unit 204 is a non-volatile device such as an HDD or SSD that stores a trained model 205 and an AI image generation program 206 for implementing generative AI. While the AI ​​image generation server 101 uses an arbitrary trained model 205 and an existing AI image generation program 206 such as Stable Diffusion as its image generation means, other image generation means may also be used. The trained model 205 and the AI ​​image generation program 206 are loaded into the RAM 202 and executed by the CPU 201. AI image generation technology is well-known, so details are omitted here. When the AI ​​image generation server 101 receives a request to generate an AI-generated image from the communication device 102 or the like, the GPU 207 executes an AI image generation process to generate the AI-generated image according to instructions from the CPU 201.

[0021] The AI-generated identification information addition unit 208 adds AI-generated identification information to the AI-generated image generated in the AI ​​image generation process to identify it as an image generated by the generation AI. This AI-generated identification information includes information indicating that the image was generated by the generation AI, information about the trained model 205 and AI image generation program 206 used, information included in the generation request, etc. The AI-generated identification information may be in the form of metadata such as header information of the image file, or may be superimposed on the image itself as an invisible digital watermark or visible text. The AI-generated image with the added AI-generated identification information is transmitted to the communication device 102 via the network 104 or stored in the storage unit 204.

[0022] The network I / F 209 is connected to the network 104 and inputs and outputs various types of information via the network 104 .

[0023] FIG. 3 is a block diagram illustrating the hardware configuration of the communication device 102. As shown in FIG.

[0024] 3, the communication device 102 includes a CPU 301, a RAM 302, an SSD 303, a user I / F unit 304, and a network I / F unit 305. These are connected to one another via a bus 306.

[0025] The CPU 301 controls the operation of the communication device 102 and operates based on a program loaded in the RAM 302. The SSD 303 stores system programs, application programs, and the like. The user I / F unit 304 includes a display, a touch panel, a keyboard, a mouse, and the like, and performs input / output processing with the user. The network I / F unit 305 may be configured to perform wired communication or wireless communication. In this embodiment, the communication device 102 may also include a call unit for realizing a telephone function, a photographing unit for realizing a camera function, and the like, in addition to the components shown in FIG. 3.

[0026] FIG. 4 is a flowchart showing the procedure of image generation processing by the generation AI in the communication system 100.

[0027] In this process, an AI-generated image is generated by the AI ​​image generation server 101 in response to a request for AI image generation from the communication device 102.

[0028] 4A is a flowchart of a generation request transmission process in the communication device 102. This process is executed by the CPU 301 by loading a program in the SSD 303 into the RAM 302, but hereinafter, the execution subject will be simply the communication device 102.

[0029] In FIG. 4(a), first, communication device 102 receives image generation parameters for generating an AI-generated image from a user (step S401). The image generation parameters are used in known AI image generation techniques, such as keywords, sentences (prompts), and images related to the image to be generated. Next, communication device 102 generates a generation request for the AI-generated image based on the received image generation parameters and transmits this generation request to AI image generation server 101 via network 104 (step S402). Thereafter, this process ends.

[0030] Figure 4(b) is a flowchart of the image generation control process in the AI ​​image generation server 101. This process is executed by the CPU 201 expanding the AI ​​image generation program 206 in the ROM 203 or memory unit 204 into the RAM 202, but hereinafter the executing entity will simply be referred to as the AI ​​image generation server 101.

[0031] 4(b), first, when the AI ​​image generation server 101 receives an image generation request from the communication device 102 via the network 104 (step S403), it controls the GPU 207 to perform AI image generation processing (step S404). As a result, an AI-generated image corresponding to the image generation parameters input by the user is generated.

[0032] Next, the AI ​​image generation server 101 controls the AI-generated identification information addition unit 208 to add AI-generated identification information to the AI-generated image generated in step S404, indicating that the image was generated by a generating AI (step S405).

[0033] After that, the AI ​​image generation server 101 transmits the AI-generated image with the AI-generated identification information added to the communication device 102 via the network 104 (step S406). Then, this process ends.

[0034] The processing in Figure 4 makes it possible to determine whether the AI-generated images in each of the following examples are AI-generated images created by a third party by referencing metadata and using image analysis.

[0035] Although the configuration using the AI ​​image generation server 101 has been described here, the configuration may also be such that the communication device 102 has a program for performing AI image generation.

[0036] Example 1 FIG. 5 is a block diagram showing a schematic network configuration of a certificate image registration system 500 according to the first embodiment, which includes a certificate image registration server 501 as a registration server of the present invention and a communication device 102. As shown in FIG.

[0037] 5, the certificate image registration system 500 is made up of a certificate image registration server 501 and a communication device 102. The certificate image registration server 501 and the communication device 102 can communicate with each other via a network 104.

[0038] In this embodiment, communication device 102 requests AI image generation from AI image generation server 101 to acquire an AI-generated image, as described above with reference to Figure 4. However, the client terminal according to this embodiment may be a different device as long as it is capable of acquiring an AI-generated image and transmitting the AI-generated image to proof image registration server 501. For example, it may be a device that connects to communication device 102 and acquires an AI-generated image from AI image generation server 101 via communication device 102.

[0039] In this embodiment, the network 104 is also communicatively connected to the AI ​​image generation server 101, although this is not shown in Figure 5. However, as long as the communication device 102 can be communicatively connected to both the AI ​​image generation server 101 and the proof image registration system 500, the AI ​​image generation server 101 and the proof image registration system 500 may each be on a different network.

[0040] FIG. 6 is a block diagram for explaining the hardware configuration of the proof image registration server 501. As shown in FIG.

[0041] 6, the proof image registration server 501 includes a CPU 601, a RAM 602, a ROM 603, a storage unit 604, a GPU 605, an AI image recognition unit 606, and a network I / F 607. These are connected to each other via a bus 608.

[0042] The CPU 601 controls the operation of the certificate image registration server 501 and operates based on a program stored in the RAM 602. The ROM 603 is a boot ROM and stores the system boot program, etc. The storage unit 604 is a non-volatile device such as an HDD or SSD and stores information necessary for certificate image registration.

[0043] The AI ​​image identification unit 606 (server-side image identification means) refers to the metadata of the proof image data included in the proof image registration information (described later) transmitted from the communication device 102, and identifies whether the image data is an AI-generated image.

[0044] The GPU 605 analyzes the image of the proof image data and identifies the target object from the image in accordance with instructions from the AI ​​image identification unit 606.

[0045] The network I / F 607 is connected to the network 104 and inputs and outputs various types of information via the network 104 .

[0046] FIG. 7 is a flowchart showing the procedure of the proof image registration process according to the first embodiment, which is executed in the proof image registration server 501.

[0047] The processing in FIG. 7 is executed by the CPU 601 reading out a program stored in the RAM 602, but hereinafter it is assumed that the execution subject is simply the certificate image registration server 501.

[0048] 7 starts when information required to register a certificate image (certification image registration information) is entered in communication device 102 and sent to certificate image registration server 501 via network 104. Note that although a registration form is exchanged between certificate image registration server 501 and communication device 102, a description thereof will be omitted in this embodiment. Note that the certificate image registration information includes the image (certification image data) itself and character strings containing personal information such as the name of the registrant.

[0049] When the certificate image registration server 501 receives the certificate image registration information sent from the communication device 102 via the network 104 at the network I / F 607, it starts the process of FIG.

[0050] When the process of FIG. 7 starts, first, the proof image registration server 501 checks whether there are any errors in the received proof image registration information (step S701). Here, the proof image registration information is checked to see if there is any excess or omission of information, and whether the input data complies with a predetermined format. Specifically, the format and size of the image are checked, and the presence or absence of full-width / half-width characters and special characters is checked for text data such as personal information. If there are any errors in the proof image registration information (Yes in step S701), the process proceeds to step S705, where a registration NG response is sent to the communication device 102, and the process of FIG. 7 is terminated. On the other hand, if there are no errors in the proof image registration information (No in step S701), the process proceeds to step S702.

[0051] In step S702, it is determined whether the image (proof image data) included in the received proof image registration information is an AI-generated image. Specifically, the AI ​​image identification unit 606 references information indicating whether the proof image data is an AI-generated image in the metadata of the proof image data, and determines whether the proof image data is an AI-generated image. If it is determined to be an AI-generated image (Yes in step S702), the process proceeds to step S705, where a registration NG is returned to the communication device 102, and the process in FIG. 7 is aborted (abortion means). On the other hand, if it is determined not to be an AI-generated image (No in step S702), the process proceeds to step S703.

[0052] In step S703, the accepted certificate image registration information is saved (registered) in the storage unit 604, and then the process proceeds to step S704, where a registration OK is returned to the communication device 102. Thereafter, the process in FIG. 7 ends.

[0053] In the process of Figure 7, a method for identifying whether proof image data is an AI-generated image is described in which metadata of the proof image data is referenced. However, there are cases where the metadata does not contain information indicating whether the image is an AI-generated image. In such cases, the AI ​​image identification unit 606 may analyze the proof image data itself using the GPU 605 and determine whether the proof image data is an AI-generated image based on the results. However, since a determination based on the results of image analysis will result in low accuracy in determining whether the proof image data is an AI-generated image, it is preferable to use a format in which the accuracy indicating the degree to which the proof image data is likely to be an AI-generated image is expressed (calculated) using a probability or score. In this case, the AI ​​image identification unit 606 converts the accuracy indicating the likelihood of the image being an AI-generated image into a percentage, and if it is equal to or greater than a threshold (e.g., N% or greater), it is determined to be an AI-generated image, and if it is less than the threshold, it is determined not to be an AI-generated image.

[0054] In addition, instead of determining whether the entire image of the proof image data is an AI-generated image, it is also possible to identify a target object from the image of the proof image data that matches the registration purpose and identify whether that target object is an AI-generated image.

[0055] Specifically, when the ID image registration system 500 is a face photo registration system, the important part of the image in the ID image data is the person part, and the background part is less important. In such a case, the AI ​​image identification unit 606 uses the GPU 605 to identify the person part (target object) from the image in the ID image data, and identifies whether the identified person part is an AI-generated image.

[0056] Furthermore, if the proof image registration system 500 is a situation photo registration system, the important part of the proof image data image is the part of the disaster area where the pointing confirmation is made. In such a case, the AI ​​image identification unit 606 uses the GPU 605 to identify the part of the disaster area (target object) where the pointing confirmation is made from the proof image data image, and identifies whether the identified part of the disaster area is an AI-generated image.

[0057] In addition, in this embodiment, in both cases where the result of step S701 is NO and where the result of step S702 is NO, the process proceeds to step S705, and a registration NG is transmitted to the communication device 102, but the present invention is not limited to this.

[0058] For example, if the result of step S701 is NO, an input information error notice may be sent to the communication device 102 in step S705 instead of registration NG. In this case, the communication device 102 displays an input information error on the display of the user I / F unit 304 in response to the error notice sent from the certificate image registration server 501, and prompts the user to re-enter the input information. Furthermore, if the input information is re-entered in response to this error display, the communication device 102 transmits the re-entered input information to the certificate image registration server 501.

[0059] Similarly, for example, if the result is NO in step S702, an error notice of the input image may be sent to the communication device 102 in step S705 instead of a registration NG. In this case, the communication device 102 displays an error in the input image on the display of the user I / F unit 304 in response to the error notice sent from the proof image registration server 501, and prompts the user to select another image. Furthermore, if another image is selected in response to this error display, the communication device 102 transmits the other image to the proof image registration server 501.

[0060] <Example 2> In Example 1, the proof image registration server 501 determines whether the proof image data included in the proof image registration information transmitted from the communication device 102 is an AI-generated image, and determines whether or not the proof image registration information can be registered. In contrast, in Example 2, the proof image registration server 501 determines whether or not the proof image registration information can be registered by running a dedicated application on the communication device 102. This example will be described in detail below.

[0061] In this embodiment, the same hardware configuration as in the first embodiment is designated by the same reference numerals, and a duplicated description will be omitted.

[0062] FIG. 8 is a flowchart illustrating a procedure of a certificate image registration process according to the second embodiment, which is executed in the communication device 102.

[0063] The processing in FIG. 8 is executed by the CPU 301 loading the certificate image registration application program stored in the SSD 303 into the RAM 302, but hereinafter, the execution subject will be simply the communication device 102.

[0064] The process of FIG. 8 starts when the certificate image registration information is input via the user I / F unit 304 of the communication device 102.

[0065] When the process of FIG. 8 starts, the communication device 102 first checks whether there are any errors in the certificate image registration information (input information) entered via the user I / F unit 304 (step S801: error identification means). The check here is the same as in step S701, so details will be omitted. If there are any errors in the input information (Yes in step S801), the process proceeds to step S802, where the input information is displayed on the display (second display means) of the user I / F unit 304 to indicate an error in the input information, and a re-entry screen prompting the user to re-enter the input information is displayed, after which the process is terminated. If the user re-enters the input information on this re-entry screen, the input information is replaced with the re-entered input information (second replacement means), and the process resumes from step S801. On the other hand, if there are no errors in the input information (No in step S801), the process proceeds to step S803. The check here may be performed for each item of input information or all at once.

[0066] In step S803, it is determined whether the input image data (input image) included in the input information is an AI-generated image (client-side image identification means). The determination here is similar to step S702, so details will be omitted, but it is preferable to use a means for referencing the metadata of the input image data as a determination method. This is because it is difficult for a typical communication device 102 to analyze the image itself and determine whether it is an AI-generated image from the analysis results. If it is determined that the input image is an AI-generated image (Yes in step S803), the process proceeds to step S804, whereas if it is determined that the input image is not an AI-generated image (No in step S803), the process proceeds to step S805.

[0067] In step S804, an error in the input image is displayed on the display (first display means) of user I / F unit 304, and an image selection screen is displayed prompting the user to select another image as the input image, after which this processing is stopped. Note that if the user selects another image on this image selection screen, the input image included in the input information is replaced with the other image selected here (first replacement means), and processing is resumed from step S803.

[0068] In step S805, the input information is sent as certificate image registration information to certificate image registration server 501 via the network I / F unit (transmission means), and then the processing in FIG. 8 is terminated.

[0069] In this embodiment, the determination method in step S803 uses a means for referencing the metadata of the input image data, but there are cases where the metadata does not contain information indicating whether or not the image is an AI-generated image. In this case, the process proceeds to step S805 without determining whether or not the input image is an AI-generated image in step S803, and the input information is sent to proof image registration server 501. In this case, proof image registration server 501 determines whether the input image is an AI-generated image by image analysis, and performs the processing from step S702 onwards.

[0070] As described above, according to the first and second embodiments, it is possible to prevent an AI-generated image from being registered in the proof image registration server 501 as a proof image.

[0071] The present invention can also be realized by supplying a program that realizes one or more functions of the present embodiment to a system or device via a network or a recording medium, and having one or more processors in the computer of the system or device read and run the program.The present invention can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

[0072] The invention is not limited to the above-described embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention.

[0073] Although the preferred embodiments of the present invention have been described above, the present invention is not limited to these embodiments, and various modifications and changes are possible within the scope of the gist of the present invention.

[0074] The disclosure of this embodiment includes the following programs, methods, and configurations. (Program 1) A program for executing registration processing of input information from a client terminal in a registration server, wherein the input information includes image data, and the program causes the computer of the registration server to function as a server-side image identification means for identifying whether the image data is an AI-generated image, and as a stop means for stopping the registration processing when the server-side image identification means identifies the image data as an AI-generated image. (Program 2) The program described in Program 1, wherein the input information includes a character string such as a registrant's name. (Program 3) A program described in Program 1 or 2, characterized in that the server-side image identification means identifies a target object that matches the registration purpose from the image data, identifies whether the target object is an AI-generated image through image analysis, and if the target object is identified as an AI-generated image, identifies the image data as an AI-generated image. (Program 4) A program described in any one of Programs 1 to 3, characterized in that the server-side image identification means calculates the probability that the image data is an AI-generated image, and if the probability is greater than or equal to a threshold, identifies the image data as an AI-generated image. (Program 5) A program described in Program 1 or 2, characterized in that the image data is attached with AI-generated identification information indicating whether it is an AI-generated image, and the server-side image identification means identifies whether the image data is an AI-generated image based on the AI-generated identification information. (Program 6) A program for executing a registration process in a client terminal, which sends input information from a user to a registration server and registers the input information on the registration server, wherein the input information includes image data, and the program causes the computer of the client terminal to function as a transmission means for sending the input information to the registration server, a client-side image identification means for identifying whether the image data is an AI-generated image before the transmission means sends the input information to the registration server, and a stop means for stopping the registration process if the client-side image identification means identifies the image data as an AI-generated image. (Program 7) The program described in Program 6, characterized in that the computer of the client terminal further functions as a first display means that displays a screen for allowing the user to select other image data as image data to be included in the input information when the client-side image identification means identifies the image data as an AI-generated image, and a first replacement means that replaces the image data included in the input information with the selected other image data when the user selects other image data on the screen displayed by the first display means, and when replacement is performed by the first replacement means, the client-side image identification means identifies whether the replaced image data is an AI-generated image or not before sending the input information to the registration server by the transmission means, and the abort means aborts the registration process when the client-side image identification means identifies the replaced image data as an AI-generated image. (Program 8) A program described in Program 6 or 7, characterized in that the computer of the client terminal is further made to function as a defect identification means that identifies whether there is a defect in the input information, and the cancellation means cancels the registration process if the defect identification means identifies that there is a defect in the input information. (Program 9) The program described in Program 8, characterized in that the computer of the client terminal further functions as a second display means that displays a screen prompting the user to re-enter the input information when the input information is identified as being incomplete by the deficiency identification means, and a second replacement means that replaces the input information with the re-entered input information when the user re-enters the input information on the screen displayed by the second display means, and when replacement is performed by the second replacement means, the deficiency identification means identifies whether the replaced input information has any deficiencies before sending the input information to the registration server by the transmission means, and the cancellation means cancels the registration process when the deficiency identification means identifies that the replaced input information has any deficiencies. (Method 1) A control method for a registration server that executes registration processing of input information from a client terminal, the input information including image data, the control method comprising: a server-side image identification step that identifies whether the image data is an AI-generated image; and an abort step that aborts the registration processing if the image data is identified as an AI-generated image in the server-side image identification step. (Method 2) A control method for a client terminal that sends input information from a user to a registration server and executes a registration process to register the input information on the registration server, wherein the input information includes image data, the control method comprising: a sending step of sending the input information to the registration server; a client-side image identification step of identifying whether the image data is an AI-generated image before sending the input information to the registration server in the sending step; and an abort step of aborting the registration process if the image data is identified as an AI-generated image in the client-side image identification step. (Configuration 1) A registration server that executes a registration process for input information from a client terminal, wherein the input information includes image data, and the registration server is characterized in that it comprises: a server-side image identification means that identifies whether the image data is an AI-generated image; and an abort means that aborts the registration process when the server-side image identification means identifies the image data as an AI-generated image. (Configuration 2) A client terminal that transmits input information from a user to a registration server and executes a registration process to register the input information on the registration server, wherein the input information includes image data, and the client terminal is characterized in that it comprises: a transmission means that transmits the input information to the registration server; a client-side image identification means that identifies whether the image data is an AI-generated image before the transmission means transmits the input information to the registration server; and an abort means that aborts the registration process when the client-side image identification means identifies the image data as an AI-generated image. [Explanation of symbols]

[0075] 102 Communication equipment 301,601 CPU 304 User I / F section 305,607 Network I / F section 306,608 buses 501 ID image registration server 605 GPU 606 AI Image Recognition Department

Claims

1. A program for executing a registration process for input information from a client terminal in a registration server, the input information includes image data; The registration server computer, a server-side image identification means for identifying whether the image data is an AI-generated image; a stop means for stopping the registration process when the image data is identified as an AI-generated image by the server-side image identification means; A program characterized by its function.

2. 2. The program according to claim 1, wherein the input information includes a character string indicating a registrant's name.

3. The server-side image identification means Identifying a target object from the image data that matches the registration purpose; Identifying whether the target object is an AI-generated image through image analysis; 2. The program according to claim 1, wherein if the target object is identified as an AI-generated image, the image data is identified as an AI-generated image.

4. The server-side image identification means Calculating the likelihood that the image data is an AI-generated image; 2. The program according to claim 1, wherein the image data is identified as an AI-generated image if the certainty is equal to or greater than a threshold value.

5. The image data is added with AI-generated identification information indicating whether it is an AI-generated image, 2. The program according to claim 1, wherein the server-side image identification means identifies whether the image data is an AI-generated image based on the AI-generated identification information.

6. A program for executing a registration process in a client terminal to transmit input information from a user to a registration server and register the input information in the registration server, the input information includes image data; The client terminal computer, a transmitting means for transmitting the input information to the registration server; a client-side image identification means for identifying whether the image data is an AI-generated image before the input information is transmitted to the registration server by the transmission means; a stop means for stopping the registration process when the image data is identified as an AI-generated image by the client-side image identification means; A program characterized by its function.

7. The client terminal computer, a first display means for displaying a screen for allowing a user to select other image data as image data to be included in the input information when the image data is identified as an AI-generated image by the client-side image identification means; a first replacement means for replacing the image data included in the input information with the selected image data when the user selects another image data on the screen displayed by the first display means; Further functioning, When the replacement is performed by the first replacement means, the client-side image identification means, before transmitting the input information to the registration server by the transmission means, identifies whether the replaced image data is an AI-generated image; 7. The program according to claim 6, wherein the halting means halts the registration process when the client-side image identification means identifies the replaced image data as an AI-generated image.

8. The client terminal computer, a defect identification means for identifying whether or not there is a defect in the input information; Further functioning, 7. The program according to claim 6, wherein the halting means halts the registration process when the defect identifying means identifies that the input information is defective.

9. The client terminal computer, a second display means for displaying a screen prompting a user to re-input the input information when the input information is identified as being incomplete by the incompleteness identification means; a second replacement means for replacing the input information with the re-inputted input information when the input information is re-input by the user on the screen displayed by the second display means; Further functioning, When the replacement is performed by the second replacement means, the defect identification means identifies whether or not there is a defect in the replaced input information before the transmission means transmits the input information to the registration server; 9. The program according to claim 8, wherein the halting means halts the registration process when the defect identifying means identifies that the input information after replacement has a defect.

10. A method for controlling a registration server that executes a registration process for input information from a client terminal, comprising: the input information includes image data; The control method includes: a server-side image identification step of identifying whether the image data is an AI-generated image; a canceling step of canceling the registration process when the image data is identified as an AI-generated image in the server-side image identification step; A control method comprising:

11. A control method for a client terminal that executes a registration process to transmit input information from a user to a registration server and register the input information in the registration server, comprising: the input information includes image data; The control method includes: a sending step of sending the input information to the registration server; a client-side image identification step of identifying whether the image data is an AI-generated image before transmitting the input information to the registration server in the transmission step; a canceling step of canceling the registration process when the image data is identified as an AI-generated image in the client-side image identification step; A control method comprising:

12. A registration server that executes a registration process for input information from a client terminal, the input information includes image data; The registration server a server-side image identification means for identifying whether the image data is an AI-generated image; a stop means for stopping the registration process when the server-side image identification means identifies the image data as an AI-generated image; A registration server comprising:

13. A client terminal that executes a registration process to transmit input information from a user to a registration server and register the input information in the registration server, the input information includes image data; The client terminal a transmitting means for transmitting the input information to the registration server; a client-side image identification means for identifying whether the image data is an AI-generated image before the input information is transmitted to the registration server by the transmission means; a stop means for stopping the registration process when the client-side image identification means identifies the image data as an AI-generated image; A client terminal comprising:

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