Information processing system, diagnostic system, and program

Abstract

To provide a system that can evaluate image quality according to the actual usage situation of a user, as compared with a configuration in which image quality is evaluated based on uniform criteria.SOLUTION: A diagnostic server acquires image data to be diagnosed, evaluates the image data for each evaluation item based on evaluation criteria for each evaluation item related to image quality, and evaluates the image data based on evaluation results for each evaluation item. The diagnostic server enables an evaluation method based on the evaluation criteria for each evaluation item to be changed according to the evaluation results for each evaluation item.SELECTED DRAWING: Figure 9

Description

[Technical field]

[0001] The present invention relates to an information processing system, a diagnostic system, and a program. [Background technology]

[0002] Patent document 1 discloses a method for predicting an overall color image quality score using image quality psychophysical quantities as variables, which represent the psychological quantities of individual image quality psychological factors that contribute to the overall color image quality score of a recording device or display device, in which the relationship between the image quality psychophysical quantities obtained for each image quality psychological factor and the overall color image quality score for an existing recording device or display device is stored in advance in a memory as statistical data, and the overall color image quality score of the recording device or display device to be evaluated is statistically predicted using the relationship between the image quality psychophysical quantities, which are the statistical data in the memory, and the overall color image quality score.

[0003] Patent document 2 discloses a method of learning the relationship between an overall image quality score determined by a subject and the characteristics of a partial image at a position on an image that the subject focuses on when determining the overall image quality score, and an image quality evaluation value calculated in accordance with such characteristics; based on the results of this learning, identifying the position of the partial image at which evaluation should be performed in terms of image quality evaluation items required to determine the overall image quality score for the image to be evaluated; calculating image quality evaluation values ​​for the image quality evaluation items required to determine the overall image quality score for the partial image information at the identified position; and calculating an overall image quality score for the image to be evaluated based on the calculated image quality evaluation value and the learning results. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 9-218956 [Patent Document 2] Japanese Patent Application Publication No. 10-63859 Summary of the Invention [Problem to be solved by the invention]

[0005] In image diagnosis, image quality is evaluated based on predetermined criteria for each item. However, since the level of image quality acceptable for each evaluation item varies from user to user, it is difficult to set a uniform criterion for image quality evaluation.

[0006] An object of the present invention is to realize a system that can evaluate image quality according to the actual usage situation of the user, as compared with a configuration that evaluates image quality based on a uniform standard. [Means for solving the problem]

[0007] The present invention according to claim 1 is one or more processors; The processor, Acquire image data of a diagnostic subject; evaluating the image data based on evaluation criteria for each evaluation item related to image quality; The evaluation method based on the evaluation criteria can be changed depending on the evaluation results for each evaluation item. The present invention relates to an information processing system. The present invention according to claim 2 is The processor, Regarding one evaluation item, if the evaluation result satisfies a predetermined condition, the evaluation item can be excluded from the evaluation targets. The information processing system according to claim 1 is characterized in that: The present invention according to claim 3 is The processor, When the evaluation result of one evaluation item satisfies a second condition different from the predetermined condition, the evaluation criteria of the evaluation item can be relaxed. The information processing system according to claim 2 is characterized in that: The present invention according to claim 4 is The processor, When the evaluation results of consecutive evaluations for one evaluation item satisfy a predetermined condition, the evaluation method for that evaluation item can be changed. The information processing system according to claim 1 is characterized in that: The present invention according to claim 5 is The processor, When the evaluation results of multiple evaluations for one evaluation item consecutively satisfy a predetermined condition, the evaluation method for that evaluation item can be changed. The information processing system according to claim 4 is characterized in that: The present invention according to claim 6 is An information processing system according to any one of claims 1 to 5; an image processing device for forming an image on a recording medium; a reading device for reading the image formed on a recording medium by the image processing device and creating image data of a diagnosis subject; The diagnostic system is characterized by comprising: The present invention according to claim 7 is On the computer, A function for acquiring image data of a diagnostic subject; A function of evaluating the image data based on evaluation criteria for each evaluation item related to image quality; A function of enabling a change of an evaluation method based on the evaluation criteria according to an evaluation result for each of the evaluation items; The present invention is a program characterized by realizing the above. Effect of the Invention

[0008] According to the invention of claim 1, it is possible to evaluate image quality according to the actual usage situation of the user, as compared with a configuration in which image quality is evaluated based on a uniform standard. According to the invention of claim 2, evaluation items that are not required by the user can be excluded from the evaluation of image quality. According to the invention of claim 3, it is possible to relax the evaluation criteria for evaluation items that the user does not consider important. According to the invention of claim 4, unlike a configuration in which a judgment is made based on the result of a single evaluation, it is possible to reflect the user's preference for image quality. According to the invention of claim 5, it is possible to eliminate cases where the evaluation result changes irregularly due to a failure or the like. According to the invention of claim 6, in diagnosing an image output by an image processing device, it is possible to evaluate the image quality according to the actual usage situation of the user. According to the invention of claim 7, in a computer having the program of the present invention installed, image quality can be evaluated according to the actual usage conditions of the user. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing a configuration of a diagnostic system to which the present embodiment is applied. [Diagram 2] FIG. 1 is a diagram illustrating a configuration of an image processing device. [Diagram 3] FIG. 2 illustrates an example of the configuration of a computer that realizes a diagnostic server. [Figure 4] FIG. 13 is a diagram illustrating an example of the configuration of a computer that realizes a terminal device. [Diagram 5] FIG. 13 is a diagram showing the procedure of evaluation by the diagnostic server. [Figure 6] FIG. 13 is a diagram showing an example of application conditions when the diagnosis result is “NG.” [Figure 7] FIG. 13 is a diagram showing an example of application conditions when the diagnosis result is "Alert." [Figure 8] FIG. 13 is a diagram showing an example of an evaluation in which the diagnosis result is “NG.” [Figure 9] FIG. 9 is a diagram showing an example of evaluation in the case where the evaluation item “soiling” is excluded from the evaluation targets in the example shown in FIG. 8. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. <System configuration> FIG. 1 is a diagram showing the configuration of a diagnostic system to which the present embodiment is applied. This diagnostic system includes an image processing device 100, a diagnostic server 200, and a terminal device 300. The image processing device 100 is a device that forms and outputs an image on a recording material such as paper using an image forming material such as toner. The image processing device 100 also has a function of reading the output image and transmitting it to the diagnostic server 200. The diagnostic server 200 is a server that evaluates the image received from the image processing device 100 and diagnoses image quality. The terminal device 300 is an information processing device that acquires the diagnostic result of the diagnostic server 200 and presents it to an administrator or the like.

[0011] The image processing device 100 and the diagnostic server 200, and the diagnostic server 200 and the terminal device 300 are connected via a network. The network is not particularly limited as long as it can be used for data communication between the devices. For example, a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, etc. may be used. The communication line used for data communication may be wired or wireless, and these may be used in combination. A gateway device, a router, an access point, or other relay device may be used to connect each device via multiple networks or communication lines. The connection between the diagnostic server 200 and the terminal device 300 may be the same network as the network used to connect the image processing device 100 and the diagnostic server 200, or a different network may be used. In addition, when the diagnostic server 200 is configured as a local server machine and is located in the same place as the terminal device 300, the diagnostic server 200 and the terminal device 300 may be directly connected to each other.

[0012] <Configuration of image processing device 100> 2 is a diagram showing the configuration of the image processing device 100. The image processing device 100 includes an image forming unit 110, an image reading unit 120, a display device 130, an operation device 140, a communication interface 150, a storage device 160, and a control device 170.

[0013] The image forming unit 110 forms an image based on image data on a recording material using an image forming material. Examples of a method for forming an image on a recording material include an electrophotographic method in which toner attached to a photoreceptor is transferred to the recording material to form an image, and an inkjet method in which ink is ejected onto the recording material to form an image.

[0014] The image reading unit 120 is configured by a so-called scanner device, optically reads an image on a set document, and generates data of the read image. Examples of image reading methods include a CCD method in which light reflected from light irradiated from a light source onto a document is reduced by a lens and received by a CCD (Charge Coupled Devices), and a CIS method in which light reflected from light irradiated in sequence from an LED (Light Emitting Diode) light source onto a document is received by a CIS (Contact Image Sensor).

[0015] The display device 130 displays information images that present various information to a user of the image processing device 100, preview images of images to be processed such as read and output, operation images for the user to perform operations, etc. The display device 130 is configured, for example, with a liquid crystal display. The display device 130 may be combined with the operation device 140 to be used as a user interface means for the user to input and output information to and from the image processing device 100.

[0016] The operation device 140 is a device for a user to perform operations such as inputting commands and data. The operation device 140 is configured, for example, by a hardware key, a touch sensor that outputs a control signal according to a position pressed or touched by a finger, etc. It may be configured as a touch panel that combines a touch sensor and a liquid crystal display that constitutes the display device 130.

[0017] The communication interface 150 is an interface for transmitting and receiving commands and data to and from an external device. An interface according to a communication method with the external device is used as the communication interface 150. The connection with the external device may be made via a network or by direct connection. The communication line may be a wired line or a wireless line. Furthermore, if the image processing device 100 has a facsimile function, the communication interface 150 includes an interface for a telephone line.

[0018] The storage device 160 stores various data, such as programs and data executed by the control device 170, image data read by the image reading unit 120, log data generated by various operations, etc. The storage device 160 is realized by a storage device such as a magnetic disk device or an SSD (Solid State Drive), for example.

[0019] The control device 170 includes a processor as a calculation means and a memory as a storage means, and performs various data processing and controls the image processing device 100 by loading a program stored in the storage device 160 into the memory and executing it. As the processor, in addition to a central processing unit (CPU), a micro processing unit (MPU), a graphics processing unit (GPU), a digital signal processor (DSP), etc. are used. As the memory, for example, a dynamic random access memory (DRAM), etc. are used.

[0020] <Configuration of diagnostic server 200> FIG. 3 is a diagram showing an example of the configuration of a computer that realizes the diagnostic server 200. The diagnostic server 200 includes one or more processors 201 that are calculation means, and a main memory 202 and an auxiliary memory 203 that are storage means. The processor 201 realizes each function of the diagnostic server 200 by loading a program stored in the auxiliary memory 203 into the main memory 202 and executing it. For example, a central processing unit (CPU), a micro processing unit (MPU), a graphics processing unit (GPU), or a digital signal processor (DSP) is used as the processor 201. For example, a random access memory (RAM) is used as the main memory 202. For example, a magnetic disk device or a solid state drive (SSD) is used as the auxiliary memory 203. The diagnostic server 200 also includes a communication interface 204 for connecting to the image processing device 100 and the terminal device 300 via a network.

[0021] The diagnostic server 200 evaluates and diagnoses the image acquired from the image processing device 100 by the processor 201 executing a program. The details of the evaluation and diagnosis of the image by the diagnostic server 200 will be described later. Note that the computer configuration shown in FIG. 3 is merely an example, and the computer realizing the diagnostic server 200 is not limited to the configuration shown in FIG. 3. For example, the configuration may include a non-volatile memory such as a flash memory or a ROM (Read Only Memory) as a storage device. Furthermore, the diagnostic server 200 is not limited to a single computer as shown in FIG. 3, but may be configured by distributing functions among multiple computers, or may be realized as a so-called cloud server constructed using resources on a network.

[0022] <Configuration of Terminal Device 300> 4 is a diagram showing an example of the configuration of a computer that realizes the terminal device 300. The terminal device 300 includes one or more processors 301, which are calculation means, and a main memory 302 and an auxiliary memory 303, which are storage means. The processor 301 realizes each function of the terminal device 300 by loading a program stored in the auxiliary memory 303 into the main memory 302 and executing it. For example, a CPU, an MPU, a GPU, a DSP, or the like is used as the processor 301. For example, a RAM is used as the main memory 302. For example, a magnetic disk device, an SSD, or the like is used as the auxiliary memory 303.

[0023] The terminal device 300 also includes a display device 304 that displays various screens, and an input device 305 on which a user performs input operations. The display device 304 is, for example, a liquid crystal display. The input device 305 is, for example, a touch sensor, a keyboard, or the like. The input device 305 may be configured as a touch panel that combines the touch sensor of the input device 305 and the liquid crystal display of the display device 304. The terminal device 300 also includes a communication interface 306 for connecting to the diagnostic server 200 via a network. For example, a smartphone, a tablet terminal, a notebook personal computer, or the like may be used as the terminal device 300. Note that the configuration of the computer shown in FIG. 4 is merely an example, and the computer used as the terminal device 300 is not limited to the configuration example of FIG. 4. For example, the configuration may include a non-volatile memory such as a flash memory or a ROM as a storage device.

[0024] <Image Evaluation and Diagnosis by Diagnostic Server 200> Next, the evaluation and diagnosis of an image by the diagnostic server 200 will be described. As a preliminary operation, an image formed on a recording material by the image forming section 110 of the image processing device 100 is output, and the output image is read by the image reading section 120 of the image processing device 100 to obtain read data (image data) of the output image. Then, this image data is transmitted from the image processing device 100 to the diagnostic server 200, and becomes the subject of evaluation and diagnosis by the diagnostic server 200.

[0025] FIG. 5 is a diagram showing the procedure of evaluation by the diagnostic server 200. The diagnostic server 200 first evaluates an image for evaluation items related to image quality divided into a plurality of categories. Then, evaluation is performed for each category based on the evaluation results for each evaluation item, and the image quality of the entire image is evaluated based on the evaluation results for each category. Evaluation for each evaluation item is performed using a score (hereinafter referred to as "evaluation score") specified according to an evaluation criterion previously set for each evaluation item. In the example shown in FIG. 5, "density", "intra-plane unevenness", "periodic unevenness", "sudden streaks", "periodic streaks", "dirt", "whiteout", etc. are set as evaluation items, and "density", "intra-plane unevenness", "defect", "noise", etc. are set as categories. The evaluation item "density" is included in the category "density". The evaluation items "intra-plane unevenness" and "periodic unevenness" are included in the category "intra-plane unevenness". The evaluation items "sudden streaks" and "periodic streaks" are included in the category "defect". The evaluation items "dirt" and "whiteout" are included in the category "noise".

[0026] As described above, the diagnostic server 200 first identifies the evaluation scores for each evaluation item for the image to be diagnosed based on the evaluation criteria for each evaluation item. The evaluation items and evaluation criteria are not particularly limited. Specifically, the diagnostic system provider or the user of the diagnostic system may set what specific evaluation items and evaluation criteria to use. Also, the user may be able to change the initial settings made by the diagnostic system provider. Similarly, regarding the classification of categories, it can be configured by the diagnostic system provider or the user. The diagnostic server 200 calculates the evaluation scores for each category based on the evaluation scores for each evaluation item identified based on the evaluation criteria, and further calculates the evaluation score for the overall image quality of the image to be diagnosed based on the evaluation scores for each category.

[0027] Here, as an example, a method of calculating the evaluation score of a category by weighting the evaluation scores of each evaluation item in the same category will be described. For example, assume that the full score of the evaluation score is 100 points, the evaluation score of the evaluation item "intra-plane unevenness" included in the category "intra-plane unevenness" shown in FIG. 5 is A1 points, and the evaluation score of the evaluation item "periodic unevenness" is A2 points. Also, assume that there is a relationship of A1 < A2 between the evaluation scores A1 and A2. Then, for the values obtained by subtracting the evaluation scores of each evaluation item from the full score of 100 points, (100 - A1) and (100 - A2), multiply them by the pre-determined weight values in descending order of the numerical values. For example, let the weight value for the largest numerical value be x1 and the weight value for the second largest numerical value be x2. Here, since A1 < A2, (100 - A1) > (100 - A2). Therefore, the calculated value of the evaluation item "intra-plane unevenness" is (100 - A1) × x1, and the calculated value of the evaluation item "periodic unevenness" is (100 - A2) × x2. Then, the value obtained by subtracting these calculated values from 100, which is the full score, is taken as the score of the category. That is, in the above case, the score of the category "intra-plane unevenness" is calculated as 100 - (100 - A1) × x1 - (100 - A2) × x2.

[0028] Similarly, evaluation scores reflecting weighting according to the evaluation score of each evaluation item are calculated for other categories. Then, an evaluation score for the entire image is calculated based on the evaluation score of each category and the weighting according to the evaluation score. Note that the above calculation method is merely one example of a method for specifying the evaluation score of a category based on the evaluation scores of the evaluation items, and the method for specifying the evaluation score of a category is not limited to the above method. Also, in the above calculation method, the specific weighting value and the number of evaluation items used to calculate the evaluation score of a category can be individually set by the provider of the diagnostic system, etc.

[0029] Next, image diagnosis based on evaluation scores will be explained. As an example, the image condition is judged into three levels: "OK," "Alert," and "NG" based on the evaluation scores of each evaluation item. "OK" is a diagnostic result indicating that no problems have occurred in any of the evaluation items. "Alert" is a diagnostic result indicating that a minor problem has occurred in one or more evaluation items. "NG" is a diagnostic result indicating that a major problem has occurred in one or more evaluation items.

[0030] The relationship between the evaluation scores of the evaluation items and the diagnostic results of the images is set, for example, as follows. "OK": Evaluation score ≥ 80 points "Alert": 80 points > evaluation score ≥ 20 points "NG": 20 points > Evaluation score In this case, if the evaluation score of any evaluation item is less than 20 points, the diagnosis result of the image will be "NG". If the evaluation scores of all evaluation items are 20 points or more but the evaluation score of any evaluation item is less than 80 points, the diagnosis result of the image will be "Alert". If the evaluation scores of all evaluation items are 80 points or more, the diagnosis result of the image will be "OK". If the diagnosis result is "Alert" or "NG", the user can identify the evaluation item that caused the diagnosis result and take measures such as changing the print settings of the image processing device 100 to improve the image quality.

[0031] When the above diagnostic result satisfies a predetermined application condition, the diagnostic server 200 prompts the user to decide whether or not to change the evaluation method for image quality. The application condition may be set based on the evaluation result (diagnosis result) in a plurality of consecutive evaluations, for example. Specific examples of the application condition will be described later.

[0032] The changes in the evaluation method are different depending on whether the diagnosis result is "Alert" or "NG." For example, when the output of an image with a diagnosis result of "NG" satisfies the application conditions, the evaluation item that caused the diagnosis result may be excluded from the evaluation targets, and when the output of an image with a diagnosis result of "Alert" satisfies the application conditions, an operation may be performed to relax the evaluation criteria for the evaluation item that caused the diagnosis result.

[0033] When the diagnostic result satisfies the application conditions, the diagnostic server 200 transmits a message to the terminal device 300 inquiring of the user whether or not to change the evaluation method when the diagnostic result is "Alert" or "NG." The user refers to the message acquired from the diagnostic server 200 using the terminal device 300, decides whether or not to change the evaluation method, and responds to the diagnostic server 200.

[0034] FIG. 6 is a diagram showing an example of the application condition when the diagnosis result is "NG". In the example shown in FIG. 6, the evaluation and diagnosis of the image are performed every 10 days, and the output of the image with the evaluation score of less than 20 points (hence the diagnosis result is "NG") for a certain evaluation item ("point C" in the figure) occurs continuously. In this example, "NG" continues for 60 days (the period shown by the dashed line in the figure) from the first occurrence of "NG", and the diagnosis result has not improved. In other words, "point C" is less than 20 points for seven consecutive times, so it is "NG". In such a case, the diagnosis server 200 transmits a message to the terminal device 300 to prompt the terminal device 300 to decide to change the evaluation method. The message may be, for example, "The evaluation item "point C" has not been improved for 60 days. Do you want to exclude this item from the calculation of the evaluation score?" The user refers to the message displayed on the terminal device 300, decides whether or not to exclude the evaluation item "point C" from the calculation of the evaluation score, and responds from the terminal device 300 to the diagnosis server 200.

[0035] For example, if a user does not consider a certain evaluation item (in this case, "point C") for an image that the user outputs, the user may not consider the deterioration of the image quality element corresponding to this evaluation item to be a problem, and may not change settings or the like to improve the image quality in the image processing device 100. As a result, as shown in Fig. 6, the evaluation score of the corresponding evaluation item in the image evaluation continues to be low. Therefore, the diagnosis server 200 prompts the user to decide whether or not to exclude the corresponding evaluation item from the evaluation targets.

[0036] FIG. 7 is a diagram showing an example of application conditions when the diagnosis result is "Alert". In the example shown in FIG. 7, image evaluation and diagnosis are performed every 10 days, and images with an evaluation score of less than 80 points (hence, the diagnosis result is "Alert") for a certain evaluation item (in the figure, "Y-plane unevenness") are output continuously. In this example, "Alert" continues for 60 days (the period shown by the dashed line in the figure) from the first "Alert" occurrence, and the diagnosis result has not improved. In other words, "Y-plane unevenness" has been less than 80 points for seven consecutive times, so it has become "Alert". In such a case, the diagnosis server 200 transmits a message to the terminal device 300 to prompt the terminal device 300 to decide to change the evaluation method. The message may be, for example, "The evaluation item "Y-plane unevenness" has not been improved for 60 days. Please check the image quality related to this item. If there is no problem with the image quality, we will change the evaluation criteria so that the image quality level output this time is OK. Is this OK?" The user refers to the message displayed on the terminal device 300, judges whether or not to relax the evaluation criteria for the evaluation item "Y-plane unevenness", and responds from the terminal device 300 to the diagnosis server 200.

[0037] The evaluation and diagnosis of images by the diagnostic server 200 have been described above, but the settings of evaluation items and categories in the above-mentioned image evaluation, the calculation method and weighting value settings of the evaluation scores of categories based on the evaluation scores of evaluation items, the calculation method and weighting value settings of the evaluation scores of images based on the evaluation scores of categories, the types of diagnostic results, and the thresholds of the evaluation scores of images associated with each diagnostic result are merely examples. Various existing methods can be applied to this embodiment as long as they are a method for evaluating an image to be diagnosed, identifying evaluation items related to image quality, and diagnosing the image based on the evaluation for each evaluation item.

[0038] <Calculation example> Next, we will present a specific example of how to calculate the evaluation score and explain the impact of changing the evaluation method on the evaluation score and the diagnosis result. As an example, we will show the impact of changing the evaluation method on the evaluation score and the diagnosis result when the diagnosis result is "NG".

[0039] FIG. 8 is a diagram showing an example of an evaluation in which the diagnosis result is "NG". In the example shown in FIG. 8, the evaluation scores of each evaluation item are shown as "density": 88 points, "intra-plane unevenness": 80 points, "periodic unevenness": 87 points, "sudden streaks": 85 points, "periodic streaks": 82 points, "stains": 19 points, and "whiteout": 89 points. In addition, the evaluation scores of each category calculated based on the evaluation scores of each evaluation item are shown as "density": 88 points, "intra-plane unevenness": 85 points, "defects": 83 points, and "noise": 30 points. And, the evaluation score of the image quality of the entire image calculated based on the evaluation scores of each category is shown as 34 points. In addition, the diagnosis result of the image is "NG". Note that the setting of the weight value used in the calculation of the evaluation score is not specified here, and only the numerical value of the calculation result is shown.

[0040] In the example shown in FIG. 8, the evaluation score for the evaluation item "dirt" is low, so the evaluation score for the category "noise" and the evaluation score for the entire image are low. The diagnosis result for the image is "NG." Here, a user of the image processing device 100 may not place importance on the presence or absence of dirt in an image output using the image processing device 100 and may tolerate dirt at the evaluation score shown in FIG. 8. In this case, even if the diagnosis result is "NG," it is considered that the user will continue to use the image processing device 100 without changing the settings to improve the image quality related to the evaluation item "dirt." Therefore, the evaluation item "dirt" is excluded from the evaluation targets.

[0041] FIG. 9 is a diagram showing an example of evaluation in the case where the evaluation item "dirt" is excluded from the evaluation target in the example shown in FIG. 8. In the example shown in FIG. 9, the evaluation score for the evaluation item "dirt" is deleted (in the figure, the numerical value is represented by a strikethrough). Therefore, the evaluation score for the category "noise" reflects only the evaluation score for the evaluation item "whiteout", which is 89 points. Then, with this change in the evaluation score for the category "noise", the evaluation score for the image quality of the entire image becomes 84 points, and the diagnosis result of the image is "OK". Therefore, the evaluation and diagnosis result of the diagnosis server 200 for the image output by the image processing device 100 are in line with the contents expected by the user of the image processing device 100, compared to the example shown in FIG. 7.

[0042] Although the embodiments of the present invention have been described above, the technical scope of the present invention is not limited to the above-mentioned embodiments. For example, in the above-mentioned embodiment, the application condition for prompting the user to decide whether or not to change the evaluation method for image quality is set based on the evaluation results (diagnosis results) in multiple consecutive evaluations. As a specific application condition, the same diagnosis result has continued for 60 days (or seven consecutive times) since the occurrence of the first diagnosis result ("NG" or "Alert"). This continuation period (continuation number) is merely an example, and other periods or numbers may be used. In addition, the application condition may be set based on the ratio of specific evaluation results or diagnosis results among diagnosis results for a certain period or a certain number of times, or the tendency of the evaluation results. After the diagnosis result of "NG" or "Alert" is issued, if the diagnosis result becomes "OK" due to a change in the settings of the image processing device 100, and "NG" or "Alert" occurs again, there is a possibility that the cause is different from the diagnosis result before the setting change. Therefore, in such a case, the diagnosis server 200 may be configured not to transmit a message prompting the user to decide whether or not to change the evaluation method for image quality.

[0043] In the above embodiment, the image formed on the recording material by the image forming unit 110 of the image processing device 100 is read by the image reading unit 120 of the same image processing device 100 to obtain image data to be diagnosed. However, the image output from the image processing device 100 may be read by another image reading device, and the obtained image data may be provided to the diagnostic server 200 as the diagnosis target. Various other modifications and alternative configurations that do not depart from the scope of the technical idea of ​​the present invention are included in the present invention.

[0044] <Additional Notes> (((1))) An information processing system comprising one or more processors, the processors acquiring image data of a diagnosis target, evaluating the image data based on evaluation criteria for each evaluation item related to image quality, and enabling a change in an evaluation method based on the evaluation criteria depending on an evaluation result for each evaluation item. (((2))) The information processing system described in (((1))) is characterized in that the processor is capable of excluding, with respect to a certain evaluation item, the evaluation item from the evaluation targets when the evaluation result satisfies a predetermined condition. (((3))) The information processing system described in (((2))) is characterized in that the processor is capable of relaxing the evaluation criteria for a certain evaluation item when the evaluation result for that evaluation item satisfies a second condition different from the predetermined condition. (((4))) The information processing system of any one of (((1))) to (((3))), wherein the processor is capable of changing the evaluation method for a given evaluation item when evaluation results in multiple consecutive evaluations for that evaluation item satisfy a predetermined condition. (((5))) The information processing system described in (((4))) is characterized in that the processor is capable of changing the evaluation method for a certain evaluation item when the evaluation results in multiple evaluations for that evaluation item consecutively satisfy a predetermined condition. (((6))) A diagnostic system comprising: an information processing system according to any one of (((1))) to (((5))); an image processing device that forms an image on a recording medium; and a reading device that reads the image formed on the recording medium by the image processing device and creates image data of a subject to be diagnosed. (((7))) A program that causes a computer to realize the following functions: acquiring image data of a diagnostic subject; evaluating the image data based on evaluation criteria for each evaluation item related to image quality; and enabling an evaluation method based on the evaluation criteria to be changed depending on the evaluation results for each evaluation item.

[0045] According to the information processing system of (((1))), it is possible to evaluate image quality according to the actual usage situation of the user, as compared with a configuration in which image quality is evaluated based on a uniform standard. According to the information processing system of (((2))), evaluation items that are not required by the user can be removed from the evaluation of image quality. According to the information processing system of (((3))), it is possible to relax the evaluation criteria for evaluation items that the user does not consider important. According to the information processing system of (((4))), unlike a configuration in which a judgment is made based on the result of a single evaluation, it is possible to reflect a user's preferences for image quality. According to the information processing system of (((5))), it is possible to eliminate cases in which the evaluation results change irregularly due to a failure or the like. According to the diagnostic system of (((6))), in diagnosing an image output by an image processing device, it is possible to evaluate the image quality according to the actual usage situation of the user. According to the program of (((7))), in a computer on which the program is installed, image quality can be evaluated according to the actual usage conditions of the user. [Explanation of symbols]

[0046] 100...image processing device, 110...image forming unit, 120...image reading unit, 130...display device, 140...operation device, 150...communication interface, 160...storage device, 170...control device, 200...diagnosis server, 201...processor, 202...main storage device, 203...auxiliary storage device, 204...communication interface, 300...terminal device, 301...processor, 302...main storage device, 303...auxiliary storage device, 304...display device, 305...input device, 306...communication interface

Claims

1. One or more processors; The processor, Acquire image data of a diagnostic subject; evaluating the image data based on evaluation criteria for each evaluation item related to image quality; The evaluation method based on the evaluation criteria can be changed depending on the evaluation results for each evaluation item. An information processing system comprising:

2. The processor, Regarding one evaluation item, if the evaluation result satisfies a predetermined condition, the evaluation item can be excluded from the evaluation targets.

2. The information processing system according to claim 1 .

3. The processor, When the evaluation result of one evaluation item satisfies a second condition different from the predetermined condition, the evaluation standard of the evaluation item can be relaxed.

3. The information processing system according to claim 2 .

4. The processor, When the evaluation results of consecutive evaluations for one evaluation item satisfy a predetermined condition, the evaluation method for that evaluation item can be changed.

2. The information processing system according to claim 1 .

5. The processor, When the evaluation results of multiple evaluations for one evaluation item consecutively satisfy a predetermined condition, the evaluation method for that evaluation item can be changed.

5. The information processing system according to claim 4.

6. An information processing system according to any one of claims 1 to 5; an image forming apparatus for forming an image on a recording medium; a reading device for reading the image formed on a recording medium by the image forming device and creating image data of a diagnosis object; A diagnostic system comprising:

7. On the computer, A function for acquiring image data of a diagnostic subject; A function of evaluating the image data based on evaluation criteria for each evaluation item related to image quality; A function of enabling a change of an evaluation method based on the evaluation criteria according to an evaluation result for each of the evaluation items; A program for realizing the above.

Images