Evaluation device, control program, evaluation system, model construction device, and evaluation method

Abstract

To evaluate authenticity of a medium with the number of levels in accordance with an attribute, or the like, of the medium.SOLUTION: An evaluation apparatus (3) includes: an image acquisition unit (351) which acquires a target image (IMGO); an information acquisition unit (352) which acquires at least one of attribute information and fine-coarse information; and an index calculation unit (353) which calculates a second index with a second number of levels in accordance with the acquired information of the information acquisition unit (352).SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an evaluation device, a control program, an evaluation system, a model construction device, and an evaluation method for evaluating the authenticity of a medium displayed in an image. [Background technology]

[0002] Conventionally, there have been known techniques for evaluating the authenticity of media such as gift certificates, various coupons, and commuter passes using images of the media. "Evaluation of authenticity" refers to indicating how close the media to be evaluated (hereinafter referred to as "target media") is to being judged to be genuine. For example, Patent Document 1 discloses a system for determining the authenticity of gift certificates by comparing gift certificate characteristic information held by the gift certificate received from a customer with gift certificate characteristic information for verification. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-70380 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the authenticity determination system disclosed in Patent Document 1 merely determines the authenticity of gift certificates received from customers, that is, it uniformly evaluates the authenticity of the gift certificate with a binary choice of 100% or 0%. Here, "100% authenticity" means that there is a 100% probability that the gift certificate received from the customer is genuine, that is, the gift certificate is genuine. "0% authenticity" means that there is a 0% probability that the gift certificate received from the customer is genuine, that is, the gift certificate is a fake.

[0005] Therefore, the authenticity determination system disclosed in Patent Document 1 is not necessarily sufficient in terms of evaluating the authenticity of the vouchers received from customers in a detailed, step-by-step manner. Furthermore, the authenticity determination system disclosed in Patent Document 1 is not necessarily sufficient in terms of reflecting the attributes of the vouchers received from customers and the needs of the person assessing the authenticity in the number of levels of authenticity evaluation. Here, attributes of the voucher include the type of voucher, validity period, area where it can be used, and store where it can be used.

[0006] One aspect of the present invention aims to evaluate the authenticity of media in general, including paper media such as gift certificates, using a number of levels that correspond to the attributes of the media or the needs of the person assessing the authenticity. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, an evaluation device according to one embodiment of the present invention comprises an image acquisition unit that acquires a target image of a target medium, an information acquisition unit that acquires at least one of attribute information indicating the attributes of the target medium and precision information regarding the precision of the evaluation of the authenticity of the target medium, and an index calculation unit that calculates an index regarding the evaluation of the authenticity of the target medium in a number of stages according to the acquired information by referring to the image acquired by the image acquisition unit and the information acquired by the information acquisition unit.

[0008] In order to solve the above-mentioned problems, an evaluation system according to one embodiment of the present invention comprises an image acquisition unit that acquires a target image of a target medium, an information acquisition unit that acquires at least one of attribute information indicating the attributes of the target medium and precision information regarding the precision of the evaluation of the authenticity of the target medium, and an index calculation unit that refers to the image acquired by the image acquisition unit and the information acquired by the information acquisition unit and outputs an index regarding the evaluation of the authenticity of the target medium in a number of stages according to the acquired information.

[0009] In order to solve the above-mentioned problems, a model construction device according to one embodiment of the present invention comprises a training data acquisition unit that acquires a dataset including an image of a medium as training data, and a model construction unit that performs machine learning using the training data to construct an evaluation model that uses a target image of the target medium as input data and outputs an index relating to the evaluation of the authenticity of the target medium in a predetermined number of stages.

[0010] In order to solve the above-mentioned problems, an evaluation method according to one aspect of the present invention includes an image acquisition step of acquiring a target image in which a target medium is captured, an information acquisition step of acquiring at least one of attribute information indicating the attributes of the target medium and precision information regarding the precision of the evaluation of the authenticity of the target medium, and an index calculation step of calculating an index regarding the evaluation of the authenticity of the target medium in a number of stages according to the acquired information by referring to the acquired image acquired in the image acquisition step and the acquired information acquired in the information acquisition step. [Effects of the Invention]

[0011] According to one aspect of the present invention, the authenticity of a medium can be evaluated using a number of stages according to the attributes of the medium or the needs of the evaluator. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram showing an example of a configuration of a main part of an evaluation system according to an embodiment of the present invention and first and second modifications thereof. [Figure 2] FIG. 2 is a diagram illustrating an example of the surface of a reference medium. [Figure 3] FIG. 10 is a diagram illustrating an example of the back side of a reference medium. [Figure 4] 10 is a flowchart illustrating an example of processing by an evaluation device according to an embodiment of the present invention. [Figure 5] FIG. 4 is a diagram showing an example of an evaluation result displayed on a display unit of the evaluation device. [Figure 6] 10 is a diagram showing an example of a state in which a target image of a target medium that is an evaluation target of the evaluation result is displayed on the display unit. FIG. [Figure 7] 10 is a diagram showing another example of a state in which a non-target image of a non-target medium that is an evaluation target of the evaluation result is displayed on the display unit. FIG. [Figure 8] FIG. 10 is a diagram showing an example of a result of whether or not use is approved, displayed on the display unit. [Figure 9] 10 is a flowchart showing an example of processing by an evaluation device according to a first modified example of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0013] [Scenes where the evaluation system can be applied] In this embodiment, a case will be described in which the administrative office of a shopping mall uses the evaluation system 100 according to one embodiment of the present invention for the purpose of managing the use of paper premium gift certificates (hereinafter abbreviated as "gift certificates") that can be used at member stores in the shopping mall. Specifically, a case will be described in which an employee at the administrative office uses the evaluation system 100 to identify the authenticity of a medium that has been applied for use as a gift certificate at a member store and to decide whether to approve the use of the medium. Hereinafter, the medium that has been applied for use as a gift certificate at a member store will be referred to as the "target medium MO," and the employee at the administrative office will be referred to as the "evaluator."

[0014] The application of the evaluation system 100 is not limited to the case of gift certificates mentioned above. The evaluation system 100 can be used to manage the use of various media such as various coupons, local currencies, commuter passes, admission tickets, vaccination tickets, prepaid cards, and three-dimensional objects (for example, fresh foods such as fish and vegetables).

[0015] [Configuration of evaluation system] The configuration of the evaluation system 100 will be described with reference to Figs. 1 to 3. The evaluation system 100 is a system for evaluating the authenticity of a target medium MO (see Fig. 6). "Authenticity" is a concept that indicates how close the object being evaluated is to the real thing. As shown in Fig. 1, the evaluation system 100 includes an image generation device 1, a model construction device 2, and an evaluation device 3.

[0016] <Configuration of image generation device> The image generating device 1 generates a target image IMGO (see FIG. 6), which is an image captured of a target medium MO. The image generating device 1 also generates a non-target image IMGN (see FIG. 7), which is an image captured of a medium other than the target medium MO. Hereinafter, a medium other than the target medium will be referred to as a "non-target medium MN (see FIG. 7)." The image generating device 1 has a communication unit 11 for wireless communication with other devices. Communication units 24 and 34, which will be described later, also have the same functions as the communication unit 11.

[0017] In this embodiment, the image generating device 1 is a scanner that reads the front surface of the target medium MO and converts it into a target image IMGO as image data. The image generating device 1 also reads a specific surface of a non-target medium MN and converts it into a non-target image IMGN as image data. The scanner serving as the image generating device 1 is assumed to be installed in each affiliated store. Note that the image generating device 1 does not have to be a scanner, and may be a device capable of capturing images, such as a digital camera, smartphone, or tablet terminal, that is not installed in each affiliated store.

[0018] As mentioned above, the target image IMGO is composed only of images of the front side of the target medium MO, and the non-target image IMGN is composed only of images of a specific side of the non-target medium MN. However, both the target image IMGO and the non-target image IMGN may be datasets composed of multiple images. For example, the target image IMGO may be a dataset of images of the front side and the back side of the target medium MO, and the non-target image IMGN may be a dataset of images of the front side and the back side of the non-target medium MN.

[0019] <Configuration of the model construction device> In this embodiment, the model construction device 2 is a management server, and is installed, for example, in a room in a building that houses the administrative office (hereinafter referred to as the "office"). The model construction device 2 does not have to be a management server, and may be built into, for example, an evaluation device 3 described below. The management server may be, for example, a server used in a known cloud service, or may be installed in the office of a company that has outsourced part or all of its operations from the administrative office. The model construction device 2 has an input unit 21, an output unit 22, a memory unit 23, a communication unit 24, and a control unit 25.

[0020] The input unit 21 accepts various operations from the evaluator. An input unit 31, which will be described later, has the same functions as the input unit 21. The output unit 22 outputs various information. The output unit 22 may be, for example, a display unit or a touch panel integrated with the input unit 21. Alternatively, for example, the output unit 22 may be a printer.

[0021] The memory unit 23 stores various information used by the model construction device 2. The memory unit 23 also stores teacher data 231 and an evaluation model 232. The teacher data 231 is a data set consisting of training images (not shown) and correct answer data. The training images are images captured of training media (not shown). The training media consist of various media, such as media that are identical to the target media MO, media that are similar to the target media MO, and media that are clearly different from the target media MO. In this embodiment, the training media are media that have previously been applied for use as gift certificates at affiliated stores.

[0022] Examples of correct answer data include the authenticity of the training medium, whether the characteristic areas of the training medium match, and whether the identification areas of the training medium match. "Authenticity of the training medium" indicates whether the training medium is genuine or fake. In this embodiment, "genuine" refers to a gift certificate that the secretariat has authorized for use at affiliated stores and registered in the model construction device 2. Hereinafter, this gift certificate will be referred to as the "reference medium MS." The reference medium MS is registered in the model construction device 2 as a set with a label indicating authorization for use and a reference image (not shown) of the reference medium MS, and this data set is recorded in a dedicated database (not shown) in the memory unit 23, thereby completing the registration of the reference medium MS.

[0023] In this embodiment, the reference medium MS will be described using the examples shown in FIGS. 2 and 3. In this embodiment, the reference image is assumed to consist only of an image of the front surface MS-1 of the reference medium MS shown in FIG. 2. Note that, like the target image IMGO and the non-target image IMGN, the reference image does not have to consist of only one image, but may also be a data set consisting of multiple images. In the example shown in FIGS. 2 and 3, the reference image may be a data set of an image of the front surface MS-1 of the reference medium MS shown in FIG. 2 and an image of the back surface MS-2 of the reference medium MS shown in FIG. 3.

[0024] Furthermore, the training images are also assumed to consist of only images of the surface of the training medium, corresponding to the target image IMGO, the non-target image IMGN, and the reference image. The training images may also be a dataset consisting of multiple images, similar to the target image IMGO.

[0025] A "characteristic area" is an area displayed on the surface of a learning medium that contains characteristic information that serves as a clue to identifying the authenticity of the learning medium. Examples of characteristic information include registration number, name, expiration date, logo, etc., and some or all of these may be lumped together to form a characteristic area. "Match / mismatch of characteristic area of ​​learning medium" indicates whether the characteristic area of ​​the learning medium matches or does not match the characteristic area of ​​the reference medium MS. Hereinafter, the characteristic area of ​​the learning medium will be referred to as the "learning characteristic area," and the characteristic area of ​​the reference medium MS will be referred to as the "reference characteristic area."

[0026] When the feature information is a character, a number, a symbol, or a combination thereof, the feature information in the training feature region and the feature information in the reference feature region are recognized, for example, by OCR (Optical Character Reader) processing. Alternatively, this feature information may be recognized by AI-OCR (Artificial Intelligence-Optical Character Reader) processing. The feature information in the training feature region recognized by OCR processing (or AI-OCR processing) is compared with the feature information in the reference feature region to determine whether the feature regions of the training medium match.

[0027] In the example of Figure 2, the area MS-3 surrounded by a dashed line on the surface MS-1 of the reference medium MS is the reference feature area. The various pieces of information displayed within this area MS-3 surrounded by a dashed line are the feature information of the reference medium MS. In this case, the area on the surface of the learning medium corresponding to the area MS-3 surrounded by a dashed line in Figure 2 is the learning feature area. The various pieces of information displayed within this learning feature area are the feature information of the learning medium.

[0028] The "identification area" is an area displayed on the surface of the learning medium that contains identification information for identifying the authenticity of the learning medium, and is, for example, a rectangular area of ​​a predetermined size. Examples of identification information include a paper pattern ID. The paper pattern ID is a predetermined feature obtained from the identification area. If the learning medium is a paper voucher, an example of the feature would be a quantity that indicates the characteristics of the raw materials of the identification area, such as the degree of entanglement of the fibers in the identification area. "Match / mismatch of the identification area of ​​the learning medium" indicates whether the identification area of ​​the learning medium matches or does not match the identification area of ​​the reference medium MS. Hereinafter, the identification area of ​​the learning medium will be referred to as the "learning identification area," and the identification area of ​​the reference medium MS will be referred to as the "reference identification area."

[0029] In the example of Figure 2, the rectangular area MS-4 on the surface MS-1 of the reference medium MS is the reference identification area. The paper pattern ID, etc. displayed within this rectangular area MS-4 becomes the identification information of the reference medium MS. In this case, the rectangular area on the surface of the learning medium that corresponds to the rectangular area MS-4 in Figure 2 becomes the learning identification area. The paper pattern ID, etc. displayed within this learning identification area becomes the identification information of the learning medium.

[0030] In this embodiment, the teacher data 231 includes a plurality of training images and is configured with the same number of basic data sets as the number of training images. The basic data sets are data sets in which training images are associated with labels as ground truth data (such as whether the training medium is authentic, whether the characteristic regions of the training medium match, and whether the discrimination regions of the training medium match).

[0031] The teacher data 231 may be stored in advance in the storage unit 23, or may be input by the evaluator via the input unit 21 and then stored in the storage unit 23. For example, the teacher data 231 may be stored in a device other than the model construction device 2. Furthermore, the model construction device 2 may generate the teacher data 231 and store it in the storage unit 23.

[0032] The evaluation model 232 is a trained model used to evaluate the authenticity of the target medium MO. The evaluation model 232 outputs a first index (described in detail below) related to the evaluation of the authenticity of the target medium MO in a predetermined number of stages. Here, since there are multiple types of gift certificates that can be used at affiliated stores depending on the amount and the type of product that can be used, there are multiple types of reference medium MS, and the training data 231 is also generated for each of the multiple types of reference medium MS. Therefore, the evaluation model 232 is also constructed for each of the multiple types of reference medium MS. Details of how the evaluation device 3 uses the evaluation model 232 will be described later.

[0033] The control unit 25 comprehensively controls each unit of the model construction device 2. The control unit 25 has a teacher data acquisition unit 251 and a model construction unit 252. The teacher data acquisition unit 251 acquires teacher data 231 from the storage unit 23 and transmits it to the model construction unit 252. The model construction unit 252 constructs an evaluation model 232 by performing machine learning with reference to the teacher data 231 acquired from the teacher data acquisition unit 251. The machine learning method and the type of evaluation model 232 are not particularly limited as long as they are capable of evaluating the authenticity of the target medium MO. For example, the model construction unit 252 may construct the evaluation model 232 using a convolutional neural network. The model construction unit 252 records the constructed evaluation model 232 in the storage unit 23.

[0034] <Configuration of evaluation device> In this embodiment, the evaluation device 3 is a desktop PC (personal computer) installed in an office. The evaluation device 3 does not have to be a desktop PC and may be, for example, a tablet terminal. The evaluation device 3 has an input unit 31, a display unit 32, a storage unit 33, a communication unit 34, and a control unit 35.

[0035] The display unit 32 displays various information. The display unit 32 also displays a second index related to the evaluation of the authenticity of the target medium MO calculated by the index calculation unit 353. Details of the index calculation unit 353 and the second index will be described later. The storage unit 33 stores various information used by the evaluation device 3. The storage unit 33 may store some or all of the various images acquired by the image acquisition unit 351 described later, the various information acquired by the information acquisition unit 352 described later, and the calculation results of the index calculation unit 353.

[0036] The control unit 35 comprehensively controls each unit of the evaluation device 3. The control unit 35 has an image acquisition unit 351, an information acquisition unit 352, an index calculation unit 353, and a display control unit 354. The image acquisition unit 351 acquires a target image IMGO or a non-target image IMGN from the image generation device 1. Hereinafter, the target image IMGO and the non-target image IMGN acquired by the image acquisition unit 351 from the image generation device 1 will be collectively referred to as the "acquired image IMGG (see FIGS. 6 and 7)." Here, an example of a case in which the image acquisition unit 351 acquires a non-target image IMGN as an acquired image IMGG is when an employee of a member store that has the image generation device 1 mistakenly sends a non-target image IMGN to the image generation device 1.

[0037] The information acquisition unit 352 acquires at least one of attribute information indicating the attributes of the target medium MO and precision information regarding the evaluation of the authenticity of the target medium MO. Examples of attribute information include the type of the target medium MO, expiration date, usable area, usable store, serial number, and, if the target medium MO is a security, the amount. The precision information indicates whether the authenticity of the target medium MO is evaluated using a fine scale or a coarse scale. For example, the authenticity of the target medium MO is evaluated using a four-scale scale of "◎, ○, △, ×" or a two-scale scale of "○, ×." The information acquisition unit 352 may acquire this information from the storage unit 33 where it is pre-stored, or may acquire this information by having the evaluator input this information via the input unit 31. The information acquisition unit 352 may also acquire information other than the attribute information and the precision information.

[0038] The index calculation unit 353 calculates a second index that classifies the evaluation of the authenticity of the target medium MO into a second number of levels, by referring to the acquired image IMGG by the image acquisition unit 351 and the acquired information by the information acquisition unit 352. In this embodiment, the index calculation unit 353 evaluates the authenticity of the target medium MO by evaluating how closely the surface of the target medium MO resembles the surface MS-1 of the reference medium MS. The acquired image IMGG includes not only the target image IMGO but also images of media that are not intended to be applied for use as gift certificates, such as non-target images IMGN.

[0039] The acquired information is mainly assumed to be composed of three cases: a case where it is composed of only attribute information, a case where it is composed of only refinement information, and a case where it is composed of attribute information and refinement information. However, the acquired information may be composed of information other than attribute information and refinement information, for example, it may be composed of various input information of the evaluator acquired by the information acquisition unit 352 via the input unit 31. The display control unit 354 controls the display on the display unit 32 in accordance with various operations accepted by the input unit 31. Details of the control of the display unit 32 by the display control unit 354 will be described later.

[0040] [Processing flow (calculation of the second index)] The flow of processing up to when the evaluation device 3 calculates the second index will be described with reference to FIG. 4. The flowchart shown in FIG. 4 is an example of an evaluation method according to one aspect of the present invention. As shown in FIG. 4, in step S101, the image generation device 1 generates a target image IMGO or a non-target image IMGN. The image generation device 1 transmits the generated target image IMGO or non-target image IMGN to the image acquisition unit 351 via the communication unit 11. In step S102 (image acquisition step), the image acquisition unit 351 acquires the target image IMGO or non-target image IMGN transmitted from the image generation device 1 via the communication unit 34. The target image IMGO or non-target image IMGN acquired by the image acquisition unit 351 becomes an acquired image IMGG. The image acquisition unit 351 transmits the acquired image IMGG to the index calculation unit 353.

[0041] In step S103 (information acquisition step), the information acquisition unit 352 acquires at least one of attribute information and refined information. At least one of the attribute information and refined information acquired by the information acquisition unit 352 becomes acquired information. The information acquisition unit 352 transmits the acquired information to the index calculation unit 353. Note that the order of the processes of steps S102 and S103 is not limited to the example in FIG. 4. For example, the process of step S102 may be executed after the process of step S103 is completed, or the processes of step S102 and step S103 may be executed simultaneously.

[0042] In step S104 (index calculation step), the index calculation unit 353 inputs the acquired image IMGG acquired from the image acquisition unit 351 into the evaluation model 232 to acquire a first index. In other words, the output data of the evaluation model 232 becomes the first index. The first index is an initial index related to the evaluation of the authenticity of the target medium MO, and has a first number of stages. Here, the evaluation model 232's original function is to evaluate the authenticity of the target medium MO, but regardless of whether the input image, which is the input data, is a target image IMGO or a non-target image IMGN, it evaluates the authenticity of the medium depicted in the input image.

[0043] As described above, in this embodiment, the processing by the index calculation unit 353 includes inputting the acquired image IMGG to the evaluation model 232 constructed by performing machine learning using a plurality of basic data sets as training data 231. Note that the first number of stages may remain unchanged regardless of updates to the evaluation model 232, or may change each time the evaluation model 232 is updated by machine learning that takes into account at least one of past attribute information and past refined / coarse information.

[0044] In step S105 (index calculation step), the index calculation unit 353 calculates the second index by reclassifying the first index into a second number of levels and acquiring the second index. The second number of levels is the number of levels after the first number of levels is reclassified. The index calculation unit 353 transmits the calculated second index to the display unit 32.

[0045] The index calculation unit 353 reclassifies the first index (hereinafter abbreviated as "reclassification") according to the acquired information acquired from the information acquisition unit 352. Specifically, the index calculation unit 353 reads the reference data table from the storage unit 33 and reclassifies the first index by comparing the acquired information with the reference data table. The reference data table is composed of attributes of the reference medium MS for each of multiple types of reference medium MS and a second level number associated with each attribute. The reference data table may be generated by referring to, for example, past attribute information and past refinement information, and may be updated as appropriate according to the accumulation of this information.

[0046] Below, several specific examples of reclassification by the index calculation unit 353 will be described. First, a first case will be described in which the first index is expressed in five levels of "A, B, C, D, E" and the price of the target medium MO included in the attribute information constituting the acquired information is 500 yen. Among the five levels, the rating "A" is assumed to be the most authentic and the rating "E" is assumed to be the least authentic. Furthermore, the acquired information is assumed to not include refinement information. In this case, if the reference data table associates "type of reference medium MO: gift certificate, usable product (attribute): some products at affiliated stores, amount (attribute): less than 1,000 yen, number of second levels: 3," the index calculation unit 353 reclassifies the first index into three levels of "A, B, C." Alternatively, the first index may be reclassified into three levels of "○, △, ×."

[0047] Next, a second case will be described in which the first index is expressed in three levels (1, 2, 3) and the price of the target medium MO included in the attribute information constituting the acquired information is 10,000 yen. Of the three levels, a rating of "1" indicates the highest authenticity, and a rating of "3" indicates the lowest authenticity. The acquired information is also assumed to be composed of attribute information and refinement information indicating "fine classification." In this case, if the reference data table associates "type of reference medium MO: gift certificate, usable products (attribute): all products at affiliated stores, amount (attribute): 5,000 yen or more, and second level number: 5," the index calculation unit 353 reclassifies the first index into five levels (1, 2, 3, 4, 5). Alternatively, the first index may be reclassified into the five levels (A, B, C, D, E) described above.

[0048] Here, if the direction of reclassification based on the reference data table (whether to classify more finely or coarsely) differs from the direction of reclassification based on the refined / coarse information that constitutes the acquired information, the index calculation unit 353 prioritizes the reclassification based on the refined / coarse information. By performing such priority processing, the index calculation unit 353 can make the second index more suited to the needs of the evaluator.

[0049] However, the index calculation unit 353 may prioritize reclassification based on the reference data table. For example, in the second case, if the acquired information is composed of attribute information and refinement information indicating "rough classification," the index calculation unit 353 reclassifies the first index into two levels of "○, ×" even if the corresponding item in the reference data table is "second number of levels: 5." Also, for example, in the second case, if the acquired information is composed of attribute information and refinement information indicating "maintain three levels," the index calculation unit 353 maintains three levels of "1, 2, 3" even if the corresponding item in the reference data table is "second number of levels: 5." In this way, reclassification by the index calculation unit 353 also includes a case where the first number of levels and the second number of levels become the same as a result of reclassifying the first index.

[0050] Next, a third case will be described in which the first index is expressed in four levels: "◎, ○, △, ×" and the acquired information consists of only precision and coarse information. In the third case, if the acquired information consists of precision and coarse information indicating, for example, "classification into three levels," the index calculation unit 353 reclassifies the first index into three levels: "○, △, ×," regardless of the attributes of the target medium MO or non-target medium MN displayed in the acquired image IMGG. On the other hand, in the third case, when the acquired information is composed of, for example, "rough classification" information, the index calculation unit 353 extracts and analyzes a characteristic image portion from the acquired image IMGG to determine the second level number. The characteristic image portion is an image portion in the acquired image IMGG that shows a characteristic region of the target medium MO or non-target medium MN. The "characteristic region" of the target medium MO or non-target medium MN is the same concept as the characteristic region of the learning medium described above.

[0051] Specifically, the index calculation unit 353 extracts and analyzes a characteristic image portion from the acquired image IMGG, thereby identifying information displayed in the characteristic image portion. Then, the index calculation unit 353 reclassifies the first index according to the identified information. For example, if the amount displayed in the characteristic image portion is identified as 100 million yen, the index calculation unit 353 determines that the amount is high and reclassifies it into a three-level category of "○, △, ×" rather than roughly reclassifying it into two levels of "○, ×."

[0052] The index calculation unit 353 determines whether the price displayed in the characteristic image portion is high, average, low, etc., using, for example, a reference data table. Specifically, the index calculation unit 353 makes the above-mentioned determination by comparing the price displayed in the characteristic image portion with the prices displayed on each of the multiple types of reference media MS that make up the reference table.

[0053] Furthermore, in the third case, when the acquired image IMGG is a non-target image IMGN, it is conceivable that the index calculation unit 353 will not be able to extract the characteristic image portion depending on the type of non-target medium MN displayed in the non-target image IMGN. When such a situation occurs, the index calculation unit 353 calculates, as the second index, an index represented only by "x" indicating that the image is a fake.

[0054] The index calculation unit 353 records the calculated second index in the storage unit 33. When the process of step S105 ends, the series of processes up to the time when the evaluation device 3 calculates the second index ends.

[0055] [Display mode of display unit] In this embodiment, after the process of step S105 in Fig. 4 is completed, when a keyboard (not shown) constituting the input unit 31 accepts a login operation, the display control unit 354 reads out a second indicator from the storage unit 33 and transmits the second indicator to the display unit 32. Then, the display control unit 354 causes the display unit 32 to display the second indicator. However, the display control unit 354 may automatically transmit the second indicator to the display unit 32 after the process of step S105 in Fig. 4 is completed, regardless of whether a login operation via the keyboard is accepted.

[0056] There are no particular limitations on the manner in which the second indicator is displayed by the display unit 32, and various variations are conceivable for this display manner. In this embodiment, the examples of FIGS. 5 to 8 will be described. As a premise, it is assumed that a home screen (not shown) is displayed on the display unit 32 during the period from the end of the processing of step S105 in FIG. 4 until the keyboard accepts a login operation. Furthermore, in the examples of FIGS. 5 to 8, it is assumed that the keyboard and a mouse (not shown) constitute the input unit 31. However, instead of a mouse, another pointing device such as a trackpad may constitute the input unit 31.

[0057] First, when the keyboard accepts a login operation, the display control unit 354 causes the display unit 32 to display a "gift certificate usage status" screen as shown in Fig. 5. Hereinafter, the "gift certificate usage status" screen will be referred to as the "usage status screen 32a." The usage status screen 32a is composed of a search screen 32b for searching for target media MO and non-target media MN that the evaluator wants to search for, and a result display screen 32c that displays the search results obtained by operating the search screen 32b.

[0058] The search screen 32b consists of the fields "Usage Status," "AI Judgment," "Application Date," and "Registration Number," as well as the buttons "Search" and "Bulk Update." In the "Usage Status" field, the evaluator selects the history of the target medium MO or non-target medium MN that they wish to search. Specifically, by accepting the movement operation of the mouse pointer displayed on the usage status screen 32a, the display control unit 354 superimposes the mouse pointer on the "Usage Status" field.

[0059] Next, when the mouse accepts a click operation while the histories are overlapping, the display control unit 354 displays a menu (not shown) above the "Usage Status" item, allowing the user to select one of the four histories. In the examples of FIGS. 5 and 8, the four histories selectable in the menu displayed in the "Usage Status" item are "Application in Progress, Approved, Rejected, and Paid." Next, when the mouse accepts a mouse pointer movement operation, the display control unit 354 causes the mouse pointer to overlap one of the four histories displayed in the menu. Next, when the mouse accepts a click operation while the histories are overlapping, the display control unit 354 selects the history overlapping with the mouse pointer and displays it in the "Usage Status" item. The display control unit 354 also records the history displayed in the "Usage Status" item in the storage unit 33.

[0060] This series of processes from accepting operations via the keyboard and mouse to display control by the display control unit 354 is all well-known. Therefore, in the following explanation, we will omit the explanation of this series of processes and will basically explain the operations of the evaluator and what is displayed on the display unit 32 in response to the operations of the evaluator.

[0061] "History" refers to the history of the target medium MO or non-target medium MN from the time a usage application is made to the affiliated store until payment is completed after use. In this specification, "the time a usage application is made to the affiliated store" refers to the time when the image acquisition unit 351 acquires the acquired image IMGG. In addition, cases where "a usage application is made to the affiliated store" also include cases where the image acquisition unit 351 acquires a non-target image IMGN as the acquired image IMGG.

[0062] "Application in progress" refers to the period from the time when the calculation process of the second index by the index calculation unit 353 is completed (the time when the processing of step S106 is completed) until the evaluator finishes identifying the authenticity of the target medium MO or non-target medium MN that has been evaluated. "Approval" refers to the period from the time when the evaluator identifies that the target medium MO that has been evaluated is the reference medium MS until the amount displayed on the reference medium MS is deposited into the secretariat's designated account. "Rejection" refers to the period from the time when the evaluator identifies that the target medium MO that has been evaluated is different from the reference medium MS. "Deposited" refers to the period from the time when the amount displayed on the reference medium MS is deposited into the secretariat's designated account.

[0063] In the "AI Judgment" field, the evaluator selects the second indicator they wish to search for. In the examples of Figures 5 and 8, a menu (not shown) is displayed above the "AI Judgment" field, displaying the second indicator in four levels: ◎, ○, △, ×. The evaluator selects the indicator they wish to search for from the menu displayed above the "AI Judgment" field. In the "Application Date" field, the evaluator inputs the application date from the keyboard, causing the application date to be displayed in that field. The display control unit 354 records the application date displayed in the "Application Date" field in the memory unit 33. The application date is the date on which the image acquisition unit 351 acquired the acquired image IMGG.

[0064] In the "Registration Number" field, the evaluator inputs the registration number from the keyboard, and the registration number is displayed in that field. The display control unit 354 records the registration number displayed in the "Registration Number" field in the storage unit 33. The registration number is a number assigned to a specified medium when it is permitted for use at an affiliated store and registered in the model construction device 2 (i.e., when the specified medium becomes the reference medium IMGG).

[0065] After completing entry into at least one of the fields "Usage Status," "AI Judgment," "Application Date," and "Registration Number," the evaluator uses the mouse to press the "Search" button. Pressing this "Search" button displays the search results on the results display screen 32c. In the example of Figure 5, the evaluator selects "Application in progress" in the "Usage Status" field and enters the period from "February 25, 2021" to "April 23, 2021" in the "Application Date" field, and then presses the "Search" button.

[0066] The result display screen 32c displays the application number, registration number, target number, history, second index, etc. of the target medium MO and non-target medium MN searched by operating the search screen 32b. The "application number" is a number assigned to the target medium MO and non-target medium MN displayed in the acquired image IMGG, and is assigned in ascending order of the acquisition date and time of the acquired image IMGG by the image acquisition unit 351. The application number is displayed in the "Application No." column on the result display screen 32c.

[0067] The "target number" is a number corresponding to the registration number of the reference medium MS displayed in the acquired image IMGG. In this embodiment, the display unit 32 displays, as the target number, the read number read by an image analysis unit (not shown) through image analysis of the acquired image IMGG. The image analysis unit is provided in the control unit 35. The display unit 32 may display, for example, a number included in attribute information acquired from the information acquisition unit 352 as the target number. Note that since non-target medium MN includes media other than gift certificates, when the acquired image IMGG is a non-target image IMGN, there may be cases where the number itself is not displayed on the non-target medium MN. In this case, the registration number and target number are not displayed on the result display screen 32c.

[0068] The history displayed in the "Usage Status" column on the result display screen 32c can be updated. Specifically, when the evaluator selects a specific "Usage Status" cell with a mouse, a menu allowing the evaluator to select one of four histories is displayed above the "Usage Status" cell, as shown in FIG. 5. Then, when the evaluator selects the appropriate latest history from the menu, the latest history is displayed in the "Usage Status" column, as shown in FIG. 8. After performing this series of mouse operations for all target media MO and non-target media MN whose histories need to be updated, the evaluator presses the "Bulk Update" button. When the "Bulk Update" button is pressed, the display control unit 354 records the latest history displayed in the "Usage Status" column in the memory unit 33.

[0069] In the "AI Judgment" column, a second indicator is displayed in four levels: "◎, ○, △, ×" for each of the target medium MO and non-target medium MN displayed in the acquired image IMGG. In this embodiment, the evaluator refers to the latest history displayed in the "Usage Status" column and the second indicator displayed in the "AI Judgment" column to finally identify the authenticity of the target medium MO and non-target medium MN displayed in the acquired image IMGG.

[0070] Specifically, when the evaluator selects a cell for a specific "Application No." using the mouse, the display control unit 354 reads out from the storage unit 33 an acquired image IMGG that shows the target medium MO or non-target medium MN that corresponds to the application number displayed in that specific "Application No." Then, the display control unit 354 stops displaying the usage status screen 32a and instead displays the read-out acquired image IMGG on the display unit 32. When displaying this acquired image IMGG, the display control unit 354 also displays the application number, registration number, target number, history, and second indicator on the display unit 32.

[0071] For example, in the example of FIG. 5, when the evaluator selects the cell for "No. 642" on the result display screen 32c, the display control unit 354 causes the display unit 32 to display the acquired image IMGG corresponding to the application number "642," as shown in FIG. 6. In the example of FIG. 6, the "usage status (history)" is "approved," while the "AI judgment (second index)" is "△." Taking these two display contents into consideration, the evaluator visually checks the acquired image IMGG displayed on the display unit 32 to finally identify its authenticity.

[0072] The medium displayed in the acquired image IMGG in FIG. 6 is the target medium MO, which is clearly a gift certificate even when visually inspected. In other words, the acquired image IMGG in FIG. 6 is the target image IMGO. In addition to the fact that the "gift certificate number (registration number)" and the "read number (target number)" match, the "usage status (history)" is "approved." Based on these facts, the evaluator is likely to ultimately approve the medium. In other words, the evaluator is likely to ultimately determine that the target medium MO displayed in the acquired image IMGG in FIG. 6 is the reference medium MS.

[0073] If the evaluator finally approves, he or she performs a mouse operation to re-display the usage status screen 32a on the display unit 32. This mouse operation causes the display control unit 354 to terminate the display of the acquired image IMGG and re-display the usage status screen 32a on the display unit 32. In the example of FIG. 6, there is no history update before and after the evaluator's final approval. Therefore, as in the example of FIG. 9, on the re-displayed usage status screen 32a, the "usage status" of "No. 642" on the result display screen 32c remains "approved."

[0074] Also, for example, in the example of FIG. 5, when the evaluator selects the cell for "No. 638" on the result display screen 32c, the display control unit 354 causes the display unit 32 to display the acquired image IMGG corresponding to the application number "638," as shown in FIG. 7. In the example of FIG. 7, the "usage status" is "application in progress," and the "AI judgment" is "x." Furthermore, neither the "gift certificate number" nor the "read number" is displayed. The evaluator visually checks the acquired image IMGG displayed on the display unit 32 while taking these displayed contents into consideration, and finally identifies the authenticity.

[0075] The medium displayed in the acquired image IMGG in FIG. 7 is a non-target medium MN, which is clearly not a gift certificate even when visually inspected. In other words, the acquired image IMGG in FIG. 7 is a non-target image IMGN. Therefore, the evaluator is likely to ultimately reject it. In other words, the evaluator is likely to ultimately determine that the non-target medium MN displayed in the acquired image IMGG in FIG. 6 is not the reference medium MS.

[0076] Even if the evaluator ultimately rejects the application, the evaluator causes the display unit 32 to redisplay the usage status screen 32a, just as if the evaluator ultimately approved the application. In the example of FIG. 7, the history is updated from "Application in progress" to "Rejected" before and after the evaluator's final rejection. Therefore, as in the example of FIG. 9, on the redisplayed usage status screen 32a, the "Usage Status" of "No. 632" on the result display screen 32c has been updated to "Rejected."

[0077] [Summary] In the evaluation system 100, the index calculation unit 353 of the evaluation device 3 calculates an index (second index) related to the evaluation of the authenticity of the target medium MO using a number of levels (second number of levels) according to the acquired information. Because the acquired information is composed of at least one of attribute information and precision information, the evaluation device 3 and evaluation system 100 can output the evaluation result of the authenticity of the target medium MO using a number of levels according to the attributes of the target medium or the needs of the evaluator.

[0078] Furthermore, in the evaluation device 3 and evaluation system 100, the index calculation unit 353 can calculate the second index using an evaluation model constructed by machine learning using the teacher data 231. Furthermore, in the evaluation system 100, the evaluation device 3 includes the display unit 32 and the display control unit 354, and can display the second index on the display unit 32 in a display mode according to the control of the display control unit 354. This allows the evaluator to easily grasp the second index, improving the convenience of the evaluation system 100.

[0079] [Modification] <First Modification> A first modified example of an evaluation system 100 according to an embodiment of the present invention will be described with reference to Figures 1, 5, and 9. For ease of explanation, components having the same functions as those described in the above embodiment are denoted by the same reference numerals, and their description will not be repeated. An evaluation system 200 according to the first modified example of the present invention shown in Figure 1 differs from the evaluation system 100 in that an index calculation unit 353a determines whether or not to execute a calculation process depending on at least one of an acquired image IMGG and acquired information.

[0080] The characteristic processing of the evaluation system 200 will be described below. The processing of steps S201 to S203 shown in FIG. 9 is the same as the processing of steps S101 to S103 shown in FIG. 4. In step S204, the index calculation unit 353a determines whether the acquired information includes processing end information. The processing end information is, for example, information indicating that the target medium MO or non-target medium MN displayed in the acquired image IMGG is different from the reference medium (i.e., is a counterfeit), and corresponds to attribute information such as "price not displayed." Another example of the processing end information is input information indicating that "authenticity will be identified visually only," acquired by the information acquisition unit 352 via the input unit 31.

[0081] If it is determined that the processing end information is included (YES in step S204), the index calculation unit 353a decides not to input the acquired image IMGG to the evaluation model 232, and transmits the decision result to the display control unit 354. In step S205, the display control unit 354 causes the display unit 32 to display an "X" indicator indicating that the target medium MO or non-target medium MN displayed in the acquired image IMGG is a fake. In addition, the display control unit 354 causes a history of "not performed" (not shown) to be displayed in the corresponding cell of "AI judgment" on the result display screen 32c shown in FIG. 5. Other display aspects on the display unit 32 are the same as those in the examples of FIGS. 5 to 8.

[0082] On the other hand, if it is determined that processing information is not included (NO in step S204), the process proceeds to step S206. In step S206, the index calculation unit 353a reads the reference image IMGG from the dedicated database in the storage unit 23 of the model construction device 2, and compares the identification information in the identification area displayed in the acquired image IMGG with the identification information in the reference identification area on the reference medium MS. Hereinafter, the identification information in the identification area displayed in the acquired image IMGG will be referred to as "target identification information," and the identification information in the reference identification area on the reference medium MS will be referred to as "reference identification information."

[0083] If it is determined that the object identification information does not match the reference identification information, or that the object identification information itself does not exist (NO in step S206), the index calculation unit 353a decides not to input the acquired image IMGG to the evaluation model 232, and transmits the decision result to the display control unit 354. After this transmission process is completed, the process proceeds to step S205.

[0084] On the other hand, if it is determined that the target identification information and the reference identification information match (YES in step S206), the index calculation unit 353a decides not to input the acquired image IMGG to the evaluation model 232, and executes the processes of steps S207 and S208. The processes of steps S207 and S208 are similar to the processes of steps S104 and S105 shown in FIG.

[0085] The end of the process of step S208 completes all of the characteristic processes of the evaluation system 200. Note that, similar to the evaluation system 100, after the process of step S208 is completed, the display control unit 354 displays the second index on the display unit 32 when the keyboard accepts a login operation.

[0086] In this way, in the evaluation system 200, the index calculation unit 353a of the evaluation device 3 does not calculate the first and second indexes depending on the contents of the acquired image IMGG and the acquired information. This prevents the evaluation system 200 (specifically, the index calculation unit 353a) from performing unnecessary calculation processes. Furthermore, the evaluation device 3 and the evaluation system 200 can evaluate the authenticity of the target medium MO or non-target medium MN displayed in the acquired image IMGG in accordance with the attributes and the needs of the evaluator.

[0087] Note that the series of processes from step S204 to S206 is merely an example, and the index calculation unit 353a may execute other processes. For example, the index calculation unit 353a may determine whether or not to execute the calculation process based only on the acquired image IMGG. Specifically, in the example of FIG. 9, the index calculation unit 353a may not execute the process of step S204, and may proceed to the process of step S206 immediately after the process of step S203 is completed. Also, for example, the index calculation unit 353a may determine whether or not to execute the calculation process based only on the acquired information. Specifically, in the example of FIG. 9, the index calculation unit 353a may not execute the process of step S206, and may proceed to the process of step S207 immediately after determining NO in step S204.

[0088] <Second Modification> A second variant of the evaluation system 100 according to one embodiment of the present invention will be described with reference to Fig. 1. The evaluation system 300 according to the second variant of the present invention shown in Fig. 1 differs from the evaluation systems 100 and 200 in that the information acquisition unit 352a acquires auxiliary information to assist in the evaluation of the authenticity of the target medium MO. Note that the evaluation system 300 also uses the auxiliary information to assist in the evaluation of the authenticity of non-target medium MN.

[0089] The auxiliary information may be any information that can assist in evaluating the authenticity of the target medium MO (and non-target medium MN). For example, the auxiliary information may be a comparison result obtained by comparing store information, including information such as the address of the affiliated store and the store owner, with the location information of the sender at the time the target image IMGO or the non-target image IMGN was sent. If the comparison result indicates a match / mismatch between the address of the affiliated store included in the store information and the address of the sender included in the location information, the comparison result can be used as reference information when evaluating authenticity. The store information may be pre-stored in the storage unit 23 of the model construction device 2. Alternatively, the evaluator may input the store information via the input unit 31 of the evaluation device 3. The comparison result described above as auxiliary information is obtained by the information acquisition unit 352a, for example, by acquiring store information and location information and comparing these pieces of information.

[0090] Furthermore, for example, the supplementary information may be suspicious information indicating facts that increase the likelihood that the target medium MO or non-target medium MN is different from the reference medium MS. For example, if multiple target media whose authenticity has been properly evaluated in the past were all requested for use during a specific time period, and the target medium MO or non-target medium MN is requested for use during a time period significantly different from the specific time period, the likelihood that they are different from the reference medium MS increases. Therefore, the fact that the target medium MO or non-target medium MN was requested for use during a time period significantly different from the specific time period can be reference information when evaluating authenticity.

[0091] In this case, the information acquisition unit 352a reads the time periods of all past usage requests (limited to those whose authenticity has been properly evaluated) from the storage unit 23 of the model construction device 2, and compares the read time periods with the time periods when usage requests for the target medium MO or non-target medium MN were made. If this comparison reveals that the read time periods are significantly different from the time periods when usage requests for the target medium MO or non-target medium MN were made, the information acquisition unit 352a acquires this fact as suspicious information.

[0092] For example, if multiple target media whose authenticity has been properly evaluated in the past have all been applied for use at a specific affiliated store, and the target image IMGO or non-target image IMGN is transmitted from a location far away from the specific affiliated store, the likelihood that it differs from the reference medium MS increases. Therefore, the fact that the location from which the target image IMGO or non-target image IMGN was transmitted is far away from the specific affiliated store can be reference information when evaluating authenticity. In this case, the method of acquiring suspicious information by the information acquisition unit 352a is the same as when the suspicious information is that the target medium MO or non-target medium MN was applied for use at a time period significantly different from a specific time period.

[0093] For example, the auxiliary information may be registration number information indicating the registration number of a gift certificate other than the reference medium MS. If the application number of the target medium MO or the application number of the non-target medium MN displayed in the acquired image IMGG matches the registration number included in the registration number information, the target medium MO or the non-target medium MN is not the reference medium MS. The registration number information may be pre-stored in the memory unit 23 of the model construction device 2. Alternatively, the evaluator may input the registration number information via the input unit 31 of the evaluation device 3. Furthermore, any of the various feature information displayed in the reference feature area of ​​the reference medium MS may be used as the auxiliary information.

[0094] The following describes the characteristic processing of the evaluation system 300. The information acquisition unit 352a acquires auxiliary information in addition to the attribute information and the refinement information, and transmits this information to the index calculation unit 353b. The index calculation unit 353b inputs the acquired image IMGG to the evaluation model 232 to acquire a first index, and then changes the evaluation result indicated by the first index by referring to the auxiliary information.

[0095] For example, if the indicator "△" is acquired as the first indicator and auxiliary information is acquired to the effect that the address of the affiliated store included in the store information does not match the address of the sender included in the location information, the indicator calculation unit 353b changes the first indicator from "△" to "×." Also, for example, if the indicator "◯" is acquired as the first indicator and auxiliary information is acquired to the effect that gift certificates with consecutive numbers and the application number of the target medium MO displayed in the acquired image are frequently used, the indicator calculation unit 353b changes the first indicator from "◯" to "◎."

[0096] Such characteristic processing of the evaluation system 300 (specifically, the index calculation unit 353b of the evaluation device 3) can improve the accuracy of the primary evaluation result of authenticity represented by the first index, thereby increasing the reliability of the evaluation result of the evaluation system 300.

[0097] Note that the index calculation unit 353b does not have to execute the process of changing the first index by referring to the auxiliary information. In this case, for example, the information acquisition unit 352a may transmit the auxiliary information to the display control unit 354, and the display control unit 354 may cause the auxiliary information to be displayed on the display unit 32. This allows the evaluator to make a final determination of authenticity by referring to the display content of the result display screen 32c and the auxiliary information displayed on the display unit 32. Furthermore, the index calculation unit 354b may determine whether or not to execute the calculation process depending on at least one of the acquired image IMGG and the acquired information. Furthermore, for example, the index calculation unit 353b may execute the process of changing the second index by referring to the auxiliary information.

[0098] <Other variations> Another modified example of the evaluation system 100 according to one embodiment of the present invention will be described. First, the image acquisition unit 351 does not have to be included in the control unit 35, and may be included in, for example, the image generation device 1. In this case, the image acquisition unit 351 transmits the target image IMGO to the index calculation unit 353 via the communication unit 11. Furthermore, the information acquisition unit 352 does not have to be included in the control unit 35, and may be included in, for example, the model construction device 2 or another device (not shown) constituting the evaluation system 100. In this case, the information acquisition unit 352 transmits at least one of the attribute information and the refinement information to the index calculation unit 353 via the communication unit 24.

[0099] In other words, it is sufficient that one or more devices constituting the evaluation system 100 are equipped with the image acquisition unit 351, the information acquisition unit 352, and the index calculation unit 353, and there are no limitations on which device these units are equipped in. Therefore, for example, the teacher data acquisition unit 251 and the model construction unit 252 of the model construction device 2 may be equipped in the control unit 35 of the evaluation device 3.

[0100] Next, in the evaluation system 100, the index calculation unit 353 does not need to use the evaluation model 232 in the calculation process of the first index. In this case, the index calculation unit 353 reads out a reference image from a dedicated database in the storage unit 23 of the model construction device 2, for example, and compares it with the acquired image IMGG. Then, the index calculation unit 353 determines the content of the first index (for example, whether it is "x" or "o") depending on how much of the area between the surface of the target medium MO or the surface of the non-target medium MN shown in the acquired image IMGG matches with the surface MS-1 of the reference medium MS.

[0101] In this case, the index calculation unit 353 may, as a process after determining the first index, calculate the second index by reclassifying the first index into a second number of levels according to the acquired information, as described above. Alternatively, the index calculation unit 353 may calculate the first index by taking into account the content of the acquired information in addition to the result of matching between the reference image and the acquired image IMGG. In other words, the index calculation unit 353 may refer to the acquired image IMGG and the acquired information and calculate some kind of index related to the evaluation of the authenticity of the target medium MO using a number of levels according to the acquired information.

[0102] [Software implementation example] The functions of the evaluation device 3 (hereinafter referred to as the "device") can be realized by a program that causes a computer to function as the device, and a program that causes a computer to function as each control block of the device (particularly each part included in the control unit 35).

[0103] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The control device and storage device execute the program, thereby realizing the functions described in each of the above-described embodiments.

[0104] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0105] In addition, some or all of the functions of the aforementioned control blocks can be realized by logic circuits. For example, an integrated circuit in which a logic circuit that functions as each of the aforementioned control blocks is formed is also included in the scope of the present invention. In addition, the functions of the aforementioned control blocks can also be realized by, for example, a quantum computer.

[0106] [Additional Notes] The present invention is not limited to the above-described embodiment and each modification, and various modifications are possible within the scope of the claims. For example, embodiments obtained by appropriately combining the technical means disclosed in the above-described embodiment and each modification are also included in the technical scope of the present invention. [Explanation of symbols]

[0107] 2. Model construction equipment 3 Evaluation equipment 100, 200, 300 rating system 231 Teacher Data 232 Evaluation Model 251 Teacher Data Acquisition Unit 252 Model Construction Department 351 Image Acquisition Unit 352, 352a Information acquisition section 353, 353a, 353b Indicator calculation section IMGG Acquired image IMGO target image MO target media

Claims

1. an image acquisition unit that acquires a target image obtained by capturing an image of the target medium; an information acquisition unit that acquires at least one of attribute information indicating the attributes of the target medium and precision information regarding the precision of an evaluation of the authenticity of the target medium; An evaluation device comprising: an index calculation unit that calculates an index for evaluating the authenticity of the target medium using a number of levels corresponding to the acquired information by referring to the image acquired by the image acquisition unit and the information acquired by the information acquisition unit.

2. The evaluation device according to claim 1, wherein the processing by the index calculation unit includes inputting the acquired image into an evaluation model constructed by performing machine learning using a dataset including an image of a medium as training data.

3. The index calculation unit inputting the acquired image into the assessment model to obtain a first initial indicator of an assessment of the authenticity of the target media, the first indicator having a first number of levels; acquiring a second index by reclassifying the first index into a second level according to the acquired information; The evaluation device according to claim 2 , further comprising: a processor for calculating the second index.

4. The evaluation device according to claim 1 , wherein the index calculation unit determines whether or not to execute processing by the index calculation unit in accordance with at least one of the acquired image and the acquired information.

5. The evaluation device according to claim 1 , wherein the information acquisition unit acquires auxiliary information for assisting in evaluation of the authenticity of the target medium.

6. The evaluation device according to claim 1 , further comprising a display unit that displays the index relating to the evaluation of the authenticity of the target medium calculated by the index calculation unit.

7. A control program for causing a computer to function as the evaluation device according to claim 1, the control program causing a computer to function as the image acquisition unit, the information acquisition unit, and the index calculation unit.

8. an image acquisition unit that acquires a target image obtained by capturing an image of the target medium; an information acquisition unit that acquires at least one of attribute information indicating the attributes of the target medium and precision information regarding the precision of an evaluation of the authenticity of the target medium; An evaluation system comprising: an index calculation unit that refers to the image acquired by the image acquisition unit and the information acquired by the information acquisition unit, and outputs an index regarding the evaluation of the authenticity of the target medium in a number of stages according to the acquired information.

9. a training data acquisition unit that acquires a data set including an image of the medium as training data; and a model construction unit that constructs an evaluation model that uses a target image of the target medium as input data by performing machine learning with reference to the training data, and outputs an index related to the evaluation of the authenticity of the target medium in a predetermined number of stages.

10. an image acquisition step of acquiring a target image of the target medium; an information acquisition step of acquiring at least one of attribute information indicating attributes of the target medium and precision information regarding the precision of an evaluation of the authenticity of the target medium; An evaluation method including an index calculation step of calculating an index relating to the evaluation of the authenticity of the target medium in a number of stages according to the acquired information by referring to the acquired image acquired in the image acquisition step and the acquired information acquired in the information acquisition step.

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