Diagnostic imaging system

Abstract

To reduce the burden of a customer engineer for grasping image quality defects at the time of image diagnosis.SOLUTION: The image diagnosis system includes one or more processors, and the one or more processors acquire an image for image diagnosis formed by an image forming apparatus to be diagnosed, detect an image quality defect in the image from the image for image diagnosis, and switch highlighting of an occurrence position of the detected image quality defect according to an event.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an imaging diagnostic system. [Background technology]

[0002] Patent Document 1 describes a problem to be solved by providing a mechanism for outputting the type of detection process so that it is possible to confirm the type of detection process for each image defect when detecting image defects using multiple types of detection processes. In order to solve this problem, Patent Document 1 discloses that the entire image of the inspection target is displayed on a result display screen, and detected defects are highlighted using a color that indicates the defect detection process that was used. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-41718 Summary of the Invention [Problem to be solved by the invention]

[0004] For example, when a customer's image forming device is experiencing problems, an image diagnostic system is utilized to diagnose the abnormality in the image forming device so that a customer engineer can quickly address the issue. This image diagnostic system detects, for example, dot or line features present in an image and identifies image quality defects that occur during image formation or image reading. The customer engineer uses the image diagnostic system to identify the faulty part based on the image quality defect and determine the appropriate response. In this case, even if the image output as a result of image diagnosis highlights the image quality defect, conventional technology only displays the image quality defect by type. Therefore, with conventional technology, the customer engineer had to measure and confirm each image quality defect one by one according to the display to confirm the problem. The present invention aims to reduce the burden on customer engineers in identifying image quality defects during image diagnosis. [Means for solving the problem]

[0005] The invention described in claim 1 is an image diagnostic system comprising one or more processors, which acquire an image for image diagnosis formed by an image forming device to be diagnosed, detect image quality defects in the image for image diagnosis, and switch the highlighting of the location where the detected image quality defect occurs depending on the event. The invention described in claim 2 is the image diagnostic system described in claim 1, characterized in that the event is a plurality of types of image quality defects, and one type of image quality defect from the plurality of types of image quality defects is highlighted and distinguished from other types of image quality defects. The invention described in claim 3 is the image diagnostic system described in claim 2, characterized in that the display mode of the highlighting differs depending on the characteristics of the one type of image quality defect. The invention described in claim 4 is the image diagnostic system described in claim 1, characterized in that the event is a plurality of image quality defects of one type, and individual image quality defects are switched and highlighted from the plurality of image quality defects of the one type. A fifth aspect of the present invention is the image diagnostic system according to the fourth aspect, wherein the display mode of the highlighting differs depending on the characteristics of the individual image quality defects. A sixth aspect of the present invention is the image diagnostic system according to the fifth aspect, wherein the characteristic of each image quality defect is the size of the image quality defect. A seventh aspect of the present invention is the image diagnostic system according to the fifth aspect, wherein the characteristic of each image quality defect is a display cycle of the individual image quality defect. The invention described in claim 8 is the image diagnostic system described in claim 1, characterized in that discrimination information for discriminating the image quality defect is obtained from the image for image diagnosis formed by the image forming device, and the discrimination information is displayed together with the highlighted display. The invention described in claim 9 is the image diagnostic system described in claim 8, characterized in that the information is for determining whether the defect is caused by image formation of a specific color among multiple color images, or whether the defect is also caused by image formation of other colors excluding the specific color. A tenth aspect of the present invention is the image diagnostic system according to the eighth aspect, wherein the discrimination information is information on whether the image is a single-sided printed image or a double-sided printed image. The invention described in claim 11 is the image diagnostic system described in claim 8, characterized in that the information is for determining defects caused by reading by the image forming device. [Effects of the Invention]

[0006] According to the invention of claim 1, the burden on customer engineers to identify image quality defects during image diagnosis can be reduced. According to the invention as set forth in claim 2, it becomes easier for the user to focus on one type of image quality defect. According to the invention as set forth in claim 3, it is possible to uniquely identify image quality defects for each type of image quality defect. According to the invention as set forth in claim 4, it becomes easier for the user to notice individual image quality defects. According to the invention as set forth in claim 5, it becomes easier to grasp the differences in the characteristics of individual image quality defects. According to the invention as set forth in claim 6, it is possible to help the user to grasp the severity of the image quality defect. According to the seventh aspect of the invention, the user can easily confirm that the image quality defects are caused by the same reason. According to the invention as set forth in claim 8, it becomes easier for the user to grasp image quality defects related to a specific image. According to the invention as set forth in claim 9, defects caused by image formation of a specific color are made more clear to the user. According to the invention as set forth in claim 10, the user can distinguish and check defects caused by the transfer unit. According to the invention as set forth in claim 11, the user can distinguish and check defects caused by reading. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is a diagram showing an image diagnostic system according to an embodiment of the present invention. [Figure 2] FIG. 2 illustrates an example of the hardware configuration of a server device. [Figure 3] FIG. 1 is a diagram illustrating an image forming apparatus. [Figure 4] FIG. 2 is a diagram illustrating a functional configuration of a server device. [Figure 5] 10 is a flowchart showing a process of the server device. [Figure 6] FIG. 10 is a diagram showing a diagnosis result output by the server device. [Figure 7] FIG. 10 is a diagram showing a first modification of the diagnosis result output by the server device. [Figure 8] FIG. 10 is a diagram showing a second modification of the diagnosis result output by the server device. [Figure 9] FIG. 10 is a diagram showing a third modification of the diagnosis result output by the server device. [Figure 10] FIG. 10 is a diagram showing a fourth modified example of the diagnosis result output by the server device. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. <Imaging diagnostic system> Fig. 1 is a diagram showing an image diagnostic system 1 according to the present embodiment. Fig. 2 is a diagram showing an example of the hardware configuration of a server device 200. Fig. 3 is a diagram for explaining an image forming device 100.

[0009] The diagnostic imaging system 1 of this embodiment includes an image forming apparatus 100 that forms an image on a sheet of paper, and a server apparatus 200 that is connected to the image forming apparatus 100 via a communication line 190. In this embodiment, the server apparatus 200 performs image diagnosis for the diagnostic imaging system 1. Furthermore, the diagnostic imaging system 1 includes a user terminal 300 that is connected to the server apparatus 200 and that accepts operations from a user.

[0010] The user terminal 300 includes a display device 310. The user terminal 300 is realized by a computer. Examples of the user terminal 300 include a PC (Personal Computer), a smartphone, and a tablet terminal.

[0011] The server device 200 is realized by a computer. 2, the server device 200 includes a processing unit 11 that executes digital calculation processing according to a program, and a secondary storage unit 12 that stores information. Note that a control unit 21 of the image forming device 100, which will be described later, has a similar configuration. The secondary storage unit 12 is realized by an existing information storage device such as an HDD (Hard Disk Drive), a semiconductor memory, or a magnetic tape.

[0012] The arithmetic processing unit 11 includes a CPU 11a as an example of a processor. The arithmetic processing unit 11 also has a RAM 11b used as a working memory for the CPU 11a, and a ROM 11c in which programs executed by the CPU 11a are stored. The arithmetic processing unit 11 also has a non-volatile memory 11d that is rewritable and can retain data even if the power supply is interrupted, and an interface unit 11e that controls each unit such as a communication unit connected to the arithmetic processing unit 11.

[0013] The nonvolatile memory 11d is configured, for example, with a battery-backed SRAM or flash memory. For example, the nonvolatile memory 11d stores associations between image quality defects and highlighting, which will be described later. The nonvolatile memory 11d also stores, for example, diagnostic images, which will be described later. The secondary storage unit 12 stores files and the like, as well as programs executed by the arithmetic processing unit 11. In this embodiment, the arithmetic processing unit 11 reads a program stored in the ROM 11c or the secondary storage unit 12, and thereby executes each process.

[0014] The program executed by the CPU 11a may be provided to the server device 200 in a state where it is stored in a computer-readable recording medium such as a magnetic recording medium (such as a magnetic tape or a magnetic disk), an optical recording medium (such as an optical disk), a magneto-optical recording medium, or a semiconductor memory. The program executed by the CPU 11a may also be provided to the server device 200 using a communication means such as the Internet.

[0015] In this specification, the term "processor" refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPU: Central Processing Unit, etc.) and dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.). Furthermore, the operations of the processor may not only be performed by a single processor, but may also be performed by multiple processors located at physically separate locations working together. The order of the operations of the processor is not limited to the order described in this embodiment, and may be changed.

[0016] Of the processes described below, the processes performed by the image forming apparatus 100 are performed by a CPU 11a provided in the control unit 21 of the image forming apparatus 100. Also, of the processes described below, the processes performed by the server apparatus 200 are performed by a CPU 11a as an example of a processor provided in the server apparatus 200. In the processing described below, the server device 200 performs processing related to image diagnosis in the image diagnosis system 1. The processing related to image diagnosis in the image diagnosis system 1 may be realized by one server device 200 or by multiple devices.

[0017] 3, image forming apparatus 100 according to the present embodiment includes a printing unit 100A and a paper discharge unit 100B. Image forming apparatus 100 also includes an image reading unit 110 that reads an image, such as a chart image, formed on paper. Paper is an example of a recording material.

[0018] The printing unit 100A includes an image forming section 20 that forms an image on a sheet of paper, and a control section 21 that controls each section of the image forming apparatus 100.

[0019] The printing unit 100A also includes an image processing unit 22. The image processing unit 22 performs image processing on the image data transmitted from the image reading unit 110.

[0020] The image reading unit 110 is a so-called scanner. The image reading unit 110 has a light source that emits light to be irradiated onto paper, and a light receiving unit such as a CCD that receives light reflected from the paper. In this embodiment, read image data (described later) is generated based on the reflected light received by the light receiving unit.

[0021] The image forming section 20 has six image forming units 30T, 30P, 30Y, 30M, 30C, and 30K (hereinafter, sometimes simply referred to as "image forming units 30") that are arranged in parallel at regular intervals.

[0022] Each image forming unit 30 has a photosensitive drum 31 on which an electrostatic latent image is formed while the photosensitive drum 31 rotates in the direction of arrow A. Each image forming unit 30 also has a charging roll 32 that charges the surface of the photosensitive drum 31. Each image forming unit 30 also has a developing device 33 that develops the electrostatic latent image formed on the photosensitive drum 31. Each image forming unit 30 also has a drum cleaner 34 that removes toner and the like from the surface of the photosensitive drum 31.

[0023] Each image forming unit 30 also has an exposure device 35 that exposes the photosensitive drum 31 of each image forming unit 30 with laser light. Note that the exposure of the photosensitive drum 31 by the exposure device 35 is not limited to using laser light. For example, a light source such as an LED (Light Emitting Diode) may be provided for each image forming unit 30, and the photosensitive drum 31 may be exposed using light emitted from this light source.

[0024] Each image forming unit 30 is configured similarly except for the toner stored in the developing device 33. Image forming units 30Y, 30M, 30C, and 30K form toner images of yellow (Y), magenta (M), cyan (C), and black (K), respectively. Furthermore, the image forming units 30T and 30P form toner images using toner corresponding to the corporate color, foam toner for Braille, fluorescent color toner, toner for improving gloss, etc. In other words, the image forming units 30T and 30P form toner images using toner of a particular color.

[0025] The image forming section 20 also has an intermediate transfer belt 41 onto which the toner images of each color formed by the photosensitive drums 31 of the image forming units 30 are transferred. Furthermore, the image forming section 20 has a primary transfer roll 42 that transfers each color toner image of each image forming unit 30 onto the intermediate transfer belt 41 at the primary transfer portion T1. The image forming unit 20 also has a secondary transfer roll 43 that transfers the color toner images transferred onto the intermediate transfer belt 41 onto a sheet of paper at a secondary transfer unit T2. Furthermore, the image forming unit 20 is provided with a belt cleaner 45 that removes toner and the like from the surface of the intermediate transfer belt 41, and a fixing device 44 that fixes the secondarily transferred image onto a sheet of paper.

[0026] The image forming unit 20 performs an image forming operation based on a control signal from the control unit 21 . Specifically, in the image forming unit 20, first, the image data input from the image reading unit 110 is subjected to image processing by the image processing unit 22, and the image data after image processing is supplied to the exposure device 35. For example, in the magenta (M) image forming unit 30M, the surface of the photosensitive drum 31 is charged by the charging roll 32, and then the exposure device 35 irradiates the photosensitive drum 31 with laser light modulated by image data obtained from the image processing unit 22.

[0027] As a result, an electrostatic latent image is formed on the photosensitive drum 31 . The formed electrostatic latent image is developed by the developing unit 33, and a magenta toner image is formed on the photosensitive drum 31. Similarly, yellow, cyan and black toner images are formed in the image forming units 30Y, 30C and 30K, and special color toner images are formed in the image forming units 30T and 30P.

[0028] The color toner images formed by each image forming unit 30 are sequentially electrostatically transferred onto an intermediate transfer belt 41 rotating in the direction of arrow B in Figure 3 by a primary transfer roll 42, forming superimposed toner images on the intermediate transfer belt 41. The superimposed toner image formed on the intermediate transfer belt 41 is transported to a secondary transfer portion T2 constituted by a secondary transfer roll 43 and a backup roll 49 as the intermediate transfer belt 41 moves.

[0029] On the other hand, the paper is taken out from, for example, a paper storage unit (not shown), and then transported to the position of the registration roll 74 via the transport path. When the superimposed toner image is transported to the secondary transfer portion T2, a sheet is supplied from the registration roll 74 to the secondary transfer portion T2 in accordance with this timing. Then, at the secondary transfer portion T2, the superimposed toner images are electrostatically transferred onto the paper sheet in a lump due to the action of a transfer electric field formed between the secondary transfer roll 43 and the backup roll 49.

[0030] Thereafter, the paper onto which the superimposed toner images have been electrostatically transferred is transported to a fixing device 44 . In the fixing device 44, the paper on which the unfixed toner image is formed is pressurized and heated, and the toner image is fixed to the paper, under the control of the control unit 21. Then, the paper that has been fixed passes through the curl correction unit 81 provided in the paper discharge unit 100B, and is then transported to a paper stacking unit (not shown). Furthermore, when images are formed on both sides of the paper, the paper is turned over by a reversing mechanism 82 provided in the paper discharge unit 100B and then supplied again to the secondary transfer roll 43. As a result, toner images are formed on both sides of the paper.

[0031] In this embodiment, when image diagnosis is performed by the image forming apparatus 100 (see FIG. 1), the control unit 21 first reads out a diagnostic image from, for example, the nonvolatile memory 11d of the server device 200. The diagnostic image is an image used for image diagnosis by the image forming apparatus 100 (see FIG. 1). Then, based on the diagnostic image, the image forming unit 20 is operated to form the diagnostic image on paper. As a result, a diagnostic paper on which the diagnostic image is formed is generated, as shown by reference numeral 1A in FIG. 1.

[0032] Once the diagnostic paper is generated, it is placed on the image reading unit 110, as shown by reference symbol 1B in FIG. 1. The image reading unit 110 then reads the diagnostic paper on which the diagnostic image is formed. This generates a read image of the diagnostic paper. The read image of the diagnostic paper is an image for image diagnosis. In this embodiment, the read image of the diagnostic paper may be referred to as a "chart image."

[0033] Then, the chart image, which is this read image, is transmitted to the server device 200 and stored in the server device 200. The server device 200 performs image diagnosis by the image diagnosis system 1 based on the chart image, which is this read image. In this embodiment, a user of the image diagnostic system 1 of this embodiment, such as a maintenance person who performs maintenance on the image forming device 100, accesses the server device 200 and refers to the results of the diagnosis made by this server device 200.

[0034] 4 is a diagram showing the functional configuration of the server device 200. The server device 200 includes a chart image acquisition unit 201, an image quality defect detection unit 202, an image quality defect isolation unit 203, a highlighting unit 204, and a chart image output unit 205.

[0035] The chart image acquisition unit 201 acquires, as a chart image, a scanned image of a diagnostic paper from the image forming apparatus 100 shown in FIG. 1, for example.

[0036] The image quality defect detection unit 202 detects image quality defects from the chart image acquired from the chart image acquisition unit 201. The image quality defect detection unit 202 detects image quality defects, for example, by comparing the diagnostic image in the nonvolatile memory 11d with the chart image. There are multiple types of image quality defects that can be detected, and the type of image quality defect differs depending on the shape of the image quality defect, such as a dot or a streak.

[0037] The image quality defect isolation unit 203 isolates the image quality defects detected by the image quality defect detection unit 202 according to the type of image quality defect. The image quality defect isolation unit 203 also isolates each type of image quality defect according to the characteristics of each individual image quality defect. Examples of the characteristics of each image quality defect include the size of each image quality defect or the cycle at which each image quality defect occurs. Information about the image quality defects isolated by the image quality defect isolation unit 203 is stored, for example, in the non-volatile memory 11d (see FIG. 2).

[0038] Furthermore, the image quality defect isolation unit 203 isolates the image quality defects detected by the image quality defect detection unit 202 by type of image quality defect. The type of image quality defect refers to the type of cause of the image quality defect. For example, image quality defects can be classified into types caused by image formation and defects caused by reading. Details of these defects will be described later. Note that, for example, a machine learning model that learns information about detected image quality defects may be used to automatically determine the type of image quality defect, the characteristics of each image quality defect, and the type of image quality defect.

[0039] The highlighting unit 204 highlights the occurrence position of each image quality defect isolated by the image quality defect isolation unit 203. The highlighting unit 204 also switches the highlighting of the occurrence position of the image quality defect depending on the event. An event is the state of an image quality defect detected from a chart image, and examples include multiple types of image quality defects detected from a chart image, multiple image quality defects of the same type, etc.

[0040] For example, suppose a case where multiple types of image quality defects are detected from a chart image. In this case, the highlighting unit 204 highlights one type of image quality defect from the multiple types of image quality defects, distinguishing it from the other types of image quality defects. Also, suppose a case where multiple image quality defects of one type are detected from a chart image. In this case, the highlighting unit 204 highlights each individual image quality defect from the multiple image quality defects of one type.

[0041] The display mode of the highlighting may vary depending on the characteristics of a certain type of image quality defect based on the association between the image quality defect and the highlighting stored in the non-volatile memory 11d. The association between the image quality defect and the highlighting is information that associates information about each image quality defect with the display mode of the highlighting to be displayed for that image quality defect. For example, the display mode of the highlighting for one type of image quality defect may be distinguished from the display mode of the highlighting for another type of image quality defect. Examples of the display mode of the highlighting include the shape of the highlighting, such as a circle or a rectangle, and the display color of the highlighting.

[0042] The chart image output unit 205 outputs a chart image in which image quality defects are highlighted by the highlighting unit 204 to the user terminal 300. The chart image output unit 205 also outputs a chart image in which image quality defects are not highlighted. The chart image output unit 205 may output information about the detected image quality defects together with the chart image.

[0043] 5 is a flowchart showing the processing of the server device 200. First, the chart image acquisition unit 201 (see FIG. 4) of the server device 200 acquires a chart image from the image forming device 100 (see FIG. 1) (step 501). Then, the image quality defect detection unit 202 (see FIG. 4) of the server device 200 detects image quality defects from the chart image (step 502).

[0044] Next, the image quality defect isolation unit 203 (see FIG. 4) of the server device 200 isolates the detected image quality defects from the chart image (step 503). Then, the server device 200 determines whether or not to highlight the image quality defects (step 504). If the image quality defects are to be highlighted (YES in step 504), the highlighting unit 204 (see FIG. 4) highlights the image quality defects (step 505). Then, the chart image output unit 205 outputs the chart image in which the image quality defects are highlighted to the user terminal 300 (see FIG. 1) (step 506). If the image quality defects are not to be highlighted (NO in step 504), the chart image output unit 205 outputs the chart image in which the image quality defects are not highlighted to the user terminal 300 (step 506).

[0045] 6(a)-(b) show the diagnosis results output by the server device 200. 6(a1)-(a3) show chart images. 6(b) shows a table in which information related to image quality defects is registered. 6(a)-(b) assume a case in which d1 and d2 are detected as linear image quality defects in the chart image. 6(a)-(b) assume a case in which d3 and d4 are detected as point-like image quality defects in the chart image. Although not shown, many other linear and point-like defects are also detected.

[0046] Fig. 6(a1) shows a chart image in which image quality defects d1 and d2 are not highlighted. Fig. 6(a2) shows a chart image in which linear image quality defects d1 and d2 are both highlighted by highlighting 500. Fig. 6(a3) shows a chart image in which, of linear image quality defects d1 and d2, d1 is highlighted by highlighting 500.

[0047] In the table of FIG. 6(b), "C" is set as the "chart image." "C" is a chart image on which a cyan (C) image is formed. Furthermore, "streaks" and "dots" are set as "details." These "streaks" and "dots" are types of image quality defects that have been detected. In this embodiment, "streaks" refer to linear image quality defects, and "dots" refer to point-like image quality defects. Furthermore, a button labeled "view" is set as the first "emphasis" for each type of image quality defect. Although not shown, information on numerous point-like defects and linear defects is set in the table of FIG. 6(b).

[0048] 6(b), "103 mm," "254 mm," "53 mm," and "175 mm" are set as the positions at which image quality defects occur. In this embodiment, the image quality defect occurring at the "103 mm" position is d1, and the image quality defect occurring at the "254 mm" position is d2. The image quality defect occurring at the "53 mm" position is d3, and the image quality defect occurring at the "175 mm" position is d4.

[0049] Furthermore, the table in Figure 6(b) includes a bar graph showing the intensity of each image quality defect as a "score." The intensity of each image quality defect is an index based on the size, density, etc. of each image quality defect. In Figure 6, the higher the intensity of the image quality defect, the higher the score. Also, a button labeled "view" is provided for each individual image quality defect as a second "emphasis."

[0050] In this embodiment, any one of the chart images shown in Figures 6(a1) to 6(a3) and the table shown in Figure 6(b) are output from the server device 200 to the user terminal 300. Then, this combined information is displayed on the display device 310 (see Figure 1) of the user terminal 300 (see Figure 1). Any of the chart images shown in Figures 6(a1) to 6(a3) can be switched by a user operation.

[0051] For example, suppose that when the chart image of Fig. 6(a1) is displayed, the user selects the "view" button for streaks as the first "emphasis." In this case, the display switches from the chart image of Fig. 6(a1) to the chart image of Fig. 6(a2). As a result, of the multiple types of image quality defects, linear defects d1 and d2 are highlighted and distinguished from point defects d3 and d4.

[0052] Also, for example, suppose that when the chart image of FIG. 6(a1) is displayed, the user selects the "view" button for d1 as a second "highlighting." In this case, the display switches from the chart image of FIG. 6(a1) to the chart image of FIG. 6(a3). As a result, d1 is separated and highlighted from the linear defects d1 and d2, which are multiple image quality defects of the same type. Note that when the chart image of FIG. 6(a3) is displayed, it is also possible to switch between and highlight individual image quality defects by selecting the "view" button for d2.

[0053] FIG. 7 illustrates a first modification of the diagnostic results output by the server device 200. In FIG. 7, a chart image is used in which images of cyan (C), yellow (Y), magenta (M), and black (K) are formed. Each of the cyan (C), yellow (Y), magenta (M), and black (K) chart images is an example of a specific image for determining image quality defects. Each chart image is also an example of an image related to image formation by the image forming apparatus 100 (see FIG. 1). In FIG. 7, it is assumed that linear defects d5 and d6 are detected in the chart image as defects resulting from image formation. Examples of defects resulting from image formation include lines, streaks, unevenness, and toner stains on the paper. Defects resulting from image formation are caused by, for example, surface defects on the photosensitive drum 31, toner adhesion during paper transport, and toner adhesion during image fixing.

[0054] In Figure 7, d5 is detected in the cyan (C) chart image, but d5 is not detected in the yellow (Y), magenta (M), or black (K) chart images. Also, d6 is detected in all of the cyan (C), yellow (Y), magenta (M), and black (K) chart images.

[0055] 7, highlighting 500 is displayed on each of the chart images of cyan (C), yellow (Y), magenta (M), and black (K). In the case of the cyan (C) chart image, highlighting 500 is displayed so as to surround each of d5 and d6 in a rectangular shape. In the case of each of the yellow (Y), magenta (M), and black (K) chart images, highlighting 500 is displayed in the same position as highlighting 500 on the cyan (C) chart image.

[0056] In this embodiment, server device 200 (see FIG. 1) acquires a specific image for discriminating image quality defects as an image for image diagnosis formed by image forming device 100 (see FIG. 1). Then, server device 200 isolates image quality defects in the specific image from the specific image and displays discrimination information for discriminating image quality defects along with highlighting. For example, server device 200 (see FIG. 1) isolates defects related to image formation by image forming device 100 from defects in a chart image. Then, server device 200 displays information for discriminating defects caused by image formation as discrimination information.

[0057] In FIG. 7, first, the server device 200 (see FIG. 1) separates defects d5 and d6 caused by image formation from defects in the chart images of each color. Then, the server device 200 (see FIG. 1) displays the chart images of each color as discrimination information. Among these, d5 is detected only in the cyan (C) chart image, and d5 is not detected in the chart images of the other colors. Therefore, it can be determined that d5 is a defect caused by image formation of cyan. On the other hand, it can be determined that d6 occurring in the chart images of each color is a defect caused by image formation of other colors excluding cyan. In other words, the chart images of each color are information for determining whether a defect is caused by image formation of a specific color among images of multiple colors, or a defect caused by image formation of other colors excluding the specific color.

[0058] 7, chart images of each color are displayed together, but a chart image of a single color may be displayed. Also, a chart image of a single color may be switched with a chart image of another color. For example, a single cyan (C) chart image may be displayed, or the cyan (C) chart image may be switched with a magenta (M) chart image. Also in Modifications 2 to 4 described below, each image may be switched.

[0059] In addition, in Fig. 7, the table of Fig. 6(b) may be displayed together with the chart images of each color. Then, character strings may be displayed in the table of Fig. 6(b) as discrimination information. For example, in the column of the table of Fig. 6(b), as "type of defect", d5 may be displayed as "defect caused by cyan image formation" and d6 may be displayed as "defect caused by other image formations except for cyan". In Modifications 2 to 4 described later, the table of Fig. 6(b) may also be displayed, and character strings may be displayed as discrimination information.

[0060] 8(a) and (b) show modified example 2 of the diagnosis result output by the server device 200. FIG. 8(a) shows a chart image with an image formed on both sides. FIG. 8(b) shows a chart image with an image formed on one side. In FIG. 8, it is assumed that linear defects d7 and d8 are detected in the chart image as defects caused by image formation. The chart image in FIG. 8(a) and the chart image in FIG. 8(b) are displayed together on the user terminal 300 (see FIG. 1).

[0061] A chart image with an image formed on one side may be simply referred to as a "chart image for single-sided printing." Furthermore, a chart image with images formed on both sides may be simply referred to as a "chart image for double-sided printing." The chart image for single-sided printing and the chart image for double-sided printing are examples of a specific image.

[0062] In the chart image for double-sided printing in FIG. 8(a), both d7 and d8 are detected. Also, in the chart image for double-sided printing in FIG. 8(a), highlighting 500 is displayed at d7 and d8. In the chart image for single-sided printing in FIG. 8(b), d7 is not detected, but d8 is detected. Also, in the chart image for single-sided printing in FIG. 8(b), highlighting 500 is displayed in the same position as in the chart image for double-sided printing in FIG. 8(a).

[0063] In this embodiment, the server device 200 (see FIG. 1) displays, as discrimination information, information for discriminating defects caused by the secondary transfer roll 43, which collectively transfers images formed by multi-color image formation onto paper. For example, in FIG. 8, a chart image for double-sided printing and a chart image for single-sided printing are displayed together as discrimination information. Of these, d7 occurs in the chart image for double-sided printing, but d7 does not occur in the chart image for single-sided printing. Here, if there is a problem such as dirt on the secondary transfer roll 43 (see FIG. 3), a defect occurs on the side opposite to the printed side. When double-sided printing is performed, defects occur on both sides. Therefore, d7 occurring in the chart image for double-sided printing can be determined to be a defect caused by the secondary transfer roll 43, which collectively transfers images onto paper. Furthermore, d8 occurring in both the chart image for double-sided printing and the chart image for single-sided printing can be determined to be a defect caused by something other than the secondary transfer roll 43.

[0064] FIG. 9 is a diagram showing a third modified example of the diagnosis result output by the server device 200. In FIG. 9, a scanned background image is displayed together with the chart images of each color described in FIG. 7. The scanned background image is, for example, an image acquired when scanning is performed without placing paper on the image scanning unit 110 (see FIG. 1). FIG. 9 assumes a case in which d9 is detected as a defect caused by scanning by the image forming device 100 (see FIG. 1), and d10 is detected as a defect caused other than scanning. For example, defects caused by scanning include dirt on the platen or the scanning surface of the sensor, or a defect in the sensor itself.

[0065] In Figure 9, d9 is detected in the cyan (C) chart image, but d9 is not detected in the yellow (Y), magenta (M), and black (K) chart images and the scanned background image. Also, d10 is detected in all of the cyan (C), yellow (Y), magenta (M), and black (K) chart images and the scanned background image.

[0066] 9, highlighting 500 is displayed on each of the cyan (C), yellow (Y), magenta (M), and black (K) chart images and the scanned background image. In the case of the cyan (C) chart image, highlighting 500 is displayed so as to surround each of d9 and d10 in a rectangular shape. In the case of each of the yellow (Y), magenta (M), and black (K) chart images and the scanned background image, highlighting 500 is displayed in the same position as highlighting 500 on the cyan (C) chart image.

[0067] In this embodiment, information for discriminating defects caused by reading by the image forming apparatus 100 is displayed as discrimination information. For example, in FIG. 9, a chart image of each color and a scanned background image are displayed together on the user terminal 300 as discrimination information. Of these, d10 is detected in the scanned background image. Therefore, it can be determined that d10 is a defect caused by reading by the image forming apparatus 100. Furthermore, d9 is not detected in the scanned background image. Therefore, it can be determined that d9 is not a defect caused by reading by the image forming apparatus 100.

[0068] FIG. 10 is a diagram showing a fourth modified example of the diagnostic result output by the server device 200. In FIG. 10, it is assumed that d11 and d12 are detected as point-like defects. d11 and d12 each represent a plurality of image quality defects. The size of each of the image quality defects d11 varies. The image quality defects d12 are distributed periodically. In FIG. 10, multiple d11 are highlighted by highlighting 500, which surrounds them in a rectangular shape. Also, in FIG. 10, highlighting 500 is displayed, which surrounds multiple d12 in a circle. In this way, in FIG. 10, the highlighting display mode differs depending on the characteristics of each image quality defect.

[0069] <Additional Notes> (((1))) one or more processors; the one or more processors: Acquire an image for image diagnosis formed by an image forming device to be diagnosed; Detecting image quality defects in the image for diagnostic imaging; Switching the highlighting of the position where the detected image quality defect occurs depending on the event. An imaging diagnostic system characterized by: (((2))) The phenomenon is a plurality of types of image quality defects, highlighting one type of image quality defect from the plurality of types of image quality defects to distinguish it from other types of image quality defects; The diagnostic imaging system according to (((1))) is characterized by: (((3))) The diagnostic imaging system according to ((1)) or ((2))), wherein the display mode of the highlighting differs depending on the characteristics of the one type of image quality defect. (((4))) the event is a plurality of image quality defects of one type, Switching and highlighting individual image quality defects from the plurality of image quality defects of the one type. The diagnostic imaging system according to (((1))) is characterized by: (((5))) The image diagnostic system according to (((4))), wherein the display mode of the highlighting differs depending on the characteristics of the individual image quality defects. (((6))) The image diagnostic system according to (((5))), wherein the characteristic of each image quality defect is the size of the each image quality defect. (((7))) The image diagnostic system according to (((5))), wherein the characteristic of each image quality defect is a display cycle of the each image quality defect. (((8))) obtaining discrimination information for discriminating the image quality defect from the image for image diagnosis formed by the image forming device; Displaying the distinguishing information together with the highlighted display. The diagnostic imaging system according to (((1))) is characterized by: (((9))) The image diagnostic system described in (((8))) is characterized in that the discrimination information is information for discriminating whether the defect is caused by image formation of a specific color among images of multiple colors, or whether the defect is caused by image formation of other colors excluding the specific color. (((10))) The image diagnostic system according to any one of (((8))) to (((9))), wherein the discrimination information is a single-sided printed image and a double-sided printed image. (((11))) The image diagnostic system according to any one of ((8))) to (((10))), wherein the discrimination information is information for discriminating defects caused by reading by the image forming device.

[0070] According to the system of (((1))), the burden on customer engineers to identify image quality defects during image diagnosis can be reduced. According to the system of (((2))), it becomes easier for the user to focus on one type of image quality defect. According to the system of (((3))), it is possible to uniquely identify image quality defects for each type of image quality defect. The system according to (((4))) makes it easier for the user to notice individual image quality defects. According to the system (((5))), it becomes easier to grasp the differences in the characteristics of individual image quality defects. The system according to (((6))) can help the user to understand the severity of the image quality defect. According to the system of (((7))), it becomes easier for the user to confirm that image quality defects are caused by the same reason. The system according to (((8))) makes it easier for a user to understand image quality defects associated with a particular image. The system according to (((9))) allows the user to more clearly identify defects caused by image formation of a specific color. According to the system of (((10))), the user can distinguish and check defects caused by the transfer unit. The system according to (((11))) allows the user to distinguish and check defects resulting from reading. [Explanation of symbols]

[0071] 100... image processing device, 110... image reading unit, 200... server device

Claims

1. one or more processors; the one or more processors: Acquire an image for image diagnosis formed by an image forming device to be diagnosed; Detecting image quality defects in the image for diagnostic imaging; Switching the highlighting of the position where the detected image quality defect occurs depending on the event. An imaging diagnostic system characterized by:

2. The phenomenon is a plurality of types of image quality defects, highlighting one type of image quality defect from the plurality of types of image quality defects to distinguish it from other types of image quality defects; 2. The diagnostic imaging system according to claim 1,

3. 3. The image diagnostic system according to claim 2, wherein the display mode of the highlighting differs depending on the characteristics of the one type of image quality defect.

4. the event is a plurality of image quality defects of one type, Switching and highlighting individual image quality defects from the plurality of image quality defects of the one type.

2. The diagnostic imaging system according to claim 1,

5. 5. The image diagnostic system according to claim 4, wherein the display mode of the highlighting varies depending on the characteristics of each of the image quality defects.

6. 6. The image diagnostic system according to claim 5, wherein the characteristic of each image quality defect is the size of the image quality defect.

7. 6. The image diagnostic system according to claim 5, wherein the characteristic of each image quality defect is a display cycle of the each image quality defect.

8. obtaining discrimination information for discriminating the image quality defect from the image for image diagnosis formed by the image forming device; Displaying the distinguishing information together with the highlighted display.

2. The diagnostic imaging system according to claim 1,

9. 9. The image diagnostic system according to claim 8, wherein the discrimination information is information for discriminating whether a defect is caused by image formation of a specific color among images of multiple colors, or whether a defect is caused by image formation of other colors excluding the specific color.

10. 9. The image diagnostic system according to claim 8, wherein the discrimination information is whether the image is a single-sided print image or a double-sided print image.

11. 9. The image diagnostic system according to claim 8, wherein the discrimination information is information for discriminating defects caused by reading by the image forming apparatus.

Images