Control device, image forming system, control method, and program

Abstract

To suppress the decline in production efficiency. [Solution] A control device for an image forming apparatus, comprising: an acquisition means (301) for acquiring image defect information indicating image defects that may occur in an image formed by the image forming apparatus; an estimation means (303) for estimating defect manifestation areas where image defects are expected to become apparent when the image forming apparatus performs printing based on the print data, based on the image defect information and the print data relating to the input print job; and a determination means (304) for determining the processing of the print data based on the estimation result by the estimation means (303).

Description

Technical Field

[0001] The present disclosure relates to a process for suppressing a decrease in production efficiency of an image forming apparatus.

Background Art

[0002] In recent years, technologies for suppressing the downtime of image forming apparatuses have emerged. In Patent Document 1, using the Mahalanobis-Taguchi method, an index value D calculated by integrating information of various sensors such as toner density and charging potential is used to present a predicted image defect to the user. By this presentation, the user can appropriately determine the timing of maintenance work such as component replacement, and the downtime of the image forming apparatus is suppressed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the technology of Patent Document 1, an image defect is predicted based on the index value D calculated by the Mahalanobis-Taguchi method. However, even if an image defect is predicted, depending on the print data, it may not be noticeable and the user may be able to tolerate it. When the user can tolerate it, printing can be continued by the image forming apparatus without performing maintenance work. However, in the prediction of image defects based on the index value D, it was not possible to handle the case where the user could tolerate it, so maintenance work was performed. As a result, there was a problem that the downtime of the image forming apparatus occurred and the production efficiency of the image forming apparatus decreased.

Means for Solving the Problems

[0005] A control device according to one aspect of the present disclosure is a control device for an image forming apparatus, comprising: acquisition means for acquiring image defect information indicating image defects that may occur in an image formed by the image forming apparatus; estimation means for estimating defect manifestation regions in which image defects are expected to become apparent when the image forming apparatus performs printing based on the print data, based on the image defect information and print data relating to an input print job; and determination means for determining processing of the print data based on the result of the estimation by the estimation means. [Effects of the Invention]

[0006] According to this disclosure, it will be possible to suppress the decline in production efficiency. [Brief explanation of the drawing]

[0007] [Figure 1] This figure shows an example of the hardware configuration of the information processing device in the first embodiment. [Figure 2] This figure shows an example of the hardware configuration of an image forming apparatus connected to the information processing device shown in Figure 1 via a network. [Figure 3] This figure shows an example of the functional configuration of the information processing device shown in Figure 1. [Figure 4] This is a flowchart illustrating the processes performed by the information processing device with the functional configuration shown in Figure 3. [Figure 5] This figure shows an example of image defect information used in the processing of S402 in Figure 4. [Figure 6] This figure shows an example of the digital halftone area ratio required to reproduce the desired brightness. [Figure 7] This is a flowchart illustrating a detailed example of the process in S403 shown in Figure 4. [Figure 8] This figure shows an example of the search region determined by the S703 process in Figure 7. [Figure 9] This figure shows an example of an image pattern in which image defects become apparent. [Figure 10] This is a flowchart illustrating a detailed example of the process in S706 shown in Figure 7. [Figure 11] It is a schematic diagram showing the effect of toner scattering around the printing position and the light diffusion effect of the toner image on the printing medium. [Figure 12] It is a diagram showing an example of the notification screen displayed in the process of S406 in FIG. 4. [Figure 13] It is a diagram showing an example of the functional configuration of the information processing apparatus in FIG. 1 when the process of acquiring image defect information is executed. [Figure 14] It is a flowchart explaining a detailed example of the process of acquiring image defect information. [Figure 15] It is a diagram showing an example of the functional configuration of the information processing apparatus in the second embodiment. [Figure 16] It is a flowchart explaining the process executed by the functional configuration of the information processing apparatus in FIG. 15. [Figure 17] It is a flowchart explaining a detailed example of the process of S1605 in FIG. 16. [Figure 18] It is a diagram showing an example of the UI (User Interface) displayed in the process of S1710 in FIG. 17. [Figure 19] It is a diagram showing an example of the functional configuration of the information processing apparatus in the third embodiment. [Figure 20] It is a flowchart explaining the process executed by the functional configuration of the information processing apparatus in FIG. 19. [Figure 21] It is a diagram showing an example of the notification screen displayed in the process of S406 in FIG. 20. [Figure 22] It is a diagram showing an example of the functional configuration of the information processing apparatus in the fourth embodiment. [Figure 23] It is a flowchart explaining the process executed by the functional configuration of the information processing apparatus in FIG. 22. [Figure 24] It is a diagram showing an example of the functional configuration of the information processing apparatus in the fifth embodiment. [Figure 25] It is a flowchart explaining the process executed by the functional configuration of the information processing apparatus in FIG. 24. [Figure 26]This is a diagram showing an example of the functional configuration of the information processing apparatus in the sixth embodiment. [Figure 27] This is a flowchart for explaining the processing executed by the functional configuration of the information processing apparatus in FIG. 26. [Figure 28] This is a flowchart for explaining a detailed example of the processing of S2707 in FIG. 27.

Embodiments for Carrying Out the Invention

[0008] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the disclosed matter, and not all combinations of features described in the following embodiments are essential for the solution means of the present disclosure. The same reference numerals are assigned to the same components.

[0009] (Overview) In recent years, even when a failure occurs in an image forming apparatus or an image defect occurs in an image formed by the image forming apparatus, a print instruction may be issued to continue printing in a form that does not affect the print output of the image forming apparatus. According to such an operation, suppression of the downtime of the image forming apparatus and efficient use of consumable members can be achieved. For example, some image forming apparatuses predict image defects that may occur in the near future due to a failure of the image forming apparatus based on various sensor signals that are detection results of various sensors arranged in the housing of the image forming apparatus. Specifically, an index value D is calculated from various sensor signals using the Mahalanobis-Taguchi method, and when the calculated index value D exceeds a threshold value, it is determined that maintenance work is required, and arrangements for maintenance personnel are made.

[0010] However, whether or not an image defect is noticeable depends on the image pattern of the image data based on the print data at the location where the image defect occurs. For example, a white streak image defect is more noticeable when it occurs in areas with high image density, but less noticeable when it occurs in areas with low image density. Therefore, if one determines whether or not an image defect is acceptable in a particular print job without considering the image pattern, it is likely that the degree of tolerance for image defects in other print jobs will not be appropriately determined. For example, when an image defect is detected in a print job that records an image pattern in which image defects are easily noticeable, it is highly likely that the user will decide that the image defect is unacceptable. In this case, even if it would still be possible to print a print job that records an image pattern in which image defects are not easily noticeable, the likelihood of maintenance work being required increases, which could reduce production efficiency. Therefore, in this disclosure, based on image defect information indicating possible image defects in the image formed by the image forming apparatus and the print data related to the input print job, the defect manifestation area in which an image defect is expected to become apparent is estimated. Furthermore, in this disclosure, the processing of the print data is determined based on the estimation result of the defect manifestation area. This operation allows for the decision not to perform maintenance work if image defects are not yet apparent, thereby reducing downtime for the image forming apparatus. Consequently, it is possible to suppress the decline in production efficiency.

[0011] (First Embodiment) This embodiment describes an information processing device connected to an electrophotographic image forming apparatus. The information processing device uses pre-stored image defects that may occur in the image forming apparatus and the image data to be printed next to estimate whether or not an image defect will be noticeable when it occurs. Subsequently, based on the estimation result, the information processing device automatically decides whether or not to have the image forming apparatus perform printing.

[0012] <Hardware configuration of information processing device 1> Figure 1 shows an example of the hardware configuration of the information processing device 1 in the first embodiment. The hardware configuration of the information processing device 1 will be described below using Figure 1.

[0013] The information processing device 1 includes a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, and a RAM (Random Access Memory) 103. The information processing device 1 also includes a display 104, an operation unit 105, an HDD (Hard Disk Drive) 106, and a NIC (Network Interface Card) 107. The CPU 101, ROM 102, RAM 103, display 104, operation unit 105, HDD 106, and NIC 107 are each connected via a general-purpose bus 108. The NIC 107 is connected to the image forming apparatus 2 via a network. Therefore, the information processing device 1 and the image forming apparatus 2 are connected via a network. A network is a communication system that enables communication between nodes connected via wired or wireless media. In the example shown in Figure 1, the information processing device 1 and the image forming apparatus 2 are each nodes. While Figure 1 illustrates an example where one image forming apparatus 2 is connected to the network, multiple image forming apparatuses 2 may be connected to the network. Furthermore, the image forming apparatus 2 is an example of an external device connected to the information processing device 1. Specifically, the image forming apparatus 2 may be an MFP (Multifunction Peripheral) that forms images using an electrophotographic method. Alternatively, the image forming apparatus 2 may be a recording device that records images using an inkjet method. The following explanation assumes that the image forming apparatus 2 forms images using an electrophotographic method.

[0014] The CPU 101 uses RAM 103 as work memory to execute the OS (operating system) and various programs stored in ROM 102, HDD 106, etc. The display 104 is composed of a panel such as an LCD or organic EL. The operation unit 105 accepts user input via, for example, a mouse, keyboard, or a touch panel stacked on the panel that makes up the display 104. The NIC 107 connects to external devices, including the image forming apparatus 2, via a network to input and output information. However, this is not limited to the connection configuration with the image forming apparatus 2; for example, the connection configuration with the image forming apparatus 2 may be USB (Universal Serial Bus). Alternatively, the connection configuration with the image forming apparatus 2 may be a PCI (Peripheral Component Interconnect) bus. Alternatively, the connection configuration with the image forming apparatus 2 may be a wireless LAN. Alternatively, the connection configuration with the image forming apparatus 2 may be Bluetooth (trademark). The CPU 101 can display a UI (User Interface) provided by a program on the display 104 and accept input from the user via the operation unit 105. Alternatively, the CPU 101 may accept user input via a web browser operated on a terminal connected to the information processing device 1. This concludes the explanation of the hardware configuration of the information processing device 1 using Figure 1.

[0015] <Example of hardware configuration of image forming apparatus 2> Figure 2 shows an example of the hardware configuration of an image forming apparatus 2 connected to the information processing device 1 shown in Figure 1 via a network. The following explanation of the hardware configuration of the image forming apparatus 2 will be based on Figure 2. The explanation of the network interface between the image forming apparatus 2 and the information processing device 1 will be omitted.

[0016] The image forming apparatus 2 in Figure 2 is an electrophotographic printer. The image forming apparatus 2 comprises photoreceptor drums 201, 202, 203, and 204, a transfer belt 205, a paper feed unit 206, a transport roller 207, a secondary transfer roller 208, a fuser roller 209, and a paper output tray 210. Each of the photoreceptor drums 201, 202, 203, and 204 forms a toner image through an imaging process (charging process, exposure process, development process, and cleaning process), and transfers the formed toner image to the transfer belt 205. In this embodiment, it is assumed that a yellow toner image is formed on the photoreceptor drum 201, a magenta toner image is formed on the photoreceptor drum 202, a cyan toner image is formed on the photoreceptor drum 203, and a black toner image is formed on the photoreceptor drum 204. In other words, each of the photoreceptor drums 201, 202, 203, and 204 forms an electrostatic latent image before forming a toner image. The transfer belt 205 transports the toner images superimposed and transferred from the photoreceptor drums 201, 202, 203, and 204 to the secondary transfer position of the secondary transfer roller 208. The paper feed unit 206 can accommodate multiple recording media stacked on top of each other. The paper feed unit 206 feeds the stored recording media to the transport roller 207 according to the print job. The transport roller 207 transports the recording media fed by the paper feed unit 206 in the following order: to the secondary transfer position of the secondary transfer roller 208, to the fixing position of the fuser roller 209, and finally to the output tray 210. The secondary transfer roller 208 transfers the toner image transferred on the transfer belt 205 onto the recording media transported by the transport roller 207 at the secondary transfer position. The recording media is transported to the nip of the fuser roller 209 by the transport roller 207. The toner image is transferred to the recording media transported to the nip of the fuser roller 209. The fuser roller 209 heats and pressurizes the recording medium via its nip, thereby fixing the toner image onto the recording medium. The output tray 210 holds the recording medium on which the toner image has been fixed by the fuser roller 209. This concludes the explanation of the hardware configuration of the image forming apparatus 2 using Figure 2. Note that the hardware configuration of the image forming apparatus 2 is just one example. For example, the hardware configuration of the image forming apparatus 2 may be one that is equipped with a single photoreceptor drum and forms only monochrome images.Alternatively, the hardware configuration of the image forming apparatus 2 may include a special-color photosensitive drum in addition to the photosensitive drums 201, 202, 203, and 204. The illustration of the image reading unit, which scans chart images and the like that are printed periodically, is omitted. The image reading unit has the function of reading chart images and the like recorded on a recording medium transported in the sub-scanning direction in the main scanning direction. For example, by reading chart images and the like, the image reading unit can extract image defects contained in the images recorded on the recording medium and store them as image defect information, as described later using Figure 5.

[0017] <Functional configuration of information processing device 1> Figure 3 is a diagram showing the functional configuration of the information processing device 1 shown in Figure 1. The system configuration of the information processing device 1 will be described below using Figure 3. The functions of each part as shown in Figure 3 are realized by the CPU 101 of the information processing device 1 executing programs stored in RAM 103, etc. The information processing device 1 includes a print data acquisition unit 301, an image defect information storage unit 302, a defect manifestation area estimation unit 303, a print execution decision unit 304, a print instruction unit 305, and a print instruction result display unit 306. The print data acquisition unit 301 acquires image data to be printed next from HDD 106 or a recording medium on the Internet, etc., according to the user's instruction. The image defect information storage unit 302 acquires data on image defects that may occur in the image forming apparatus 2 in advance from the image forming apparatus 2 and stores the acquired image defect data in HDD 106. Details of the image defect data will be described later. The defect manifestation area estimation unit 303, when printing with image data acquired by the print data acquisition unit 301, estimates the area within the image data where the image defect is most noticeable as the defect manifestation area when an image defect occurs. The estimation is based on the image data and data on possible image defects acquired from the image defect information holding unit 302. Details of the defect manifestation area will be described later. The print execution decision unit 304 decides whether or not to execute printing based on the defect manifestation area estimated by the defect manifestation area estimation unit 303. The print instruction unit 305 issues a print instruction to the image forming apparatus 2 if it decides to execute printing based on the print execution decision of the print execution decision unit 304. The print instruction result display unit 306 displays on the display 104 whether or not the print instruction unit 305 issued a print instruction. This concludes the explanation of the system configuration of the information processing device 1 using Figure 3.

[0018] <Processing flow in information processing device 1> Figure 4 is a flowchart illustrating the processes executed in the functional configuration of the information processing device 1 shown in Figure 3. The details of the processes executed by the information processing device 1 will be explained below using Figure 4. The processes shown in Figure 4 are realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The processes shown in Figure 4 are executed when instructions are received from the user via the operation unit 105 in Figure 1. Note that some or all of the steps in Figure 4 may be implemented by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process indicates a step in the flowchart. Furthermore, the processes shown in Figure 4 can also be implemented as a cloud computing configuration where a single function is shared and processed collaboratively by multiple resources via the internet, as long as they realize each function of the information processing device 1 shown in Figure 3.

[0019] In S401, the CPU 101 acquires the print data to be printed next. Specifically, the print data acquisition unit 301 acquires the print data to be printed next from a recording medium on the Internet or the like, based on instructions from the user. In this embodiment, the print data is assumed to be as follows: an 8-bit CMYK image file with a print size of A4 (297mm x 210mm) and a resolution of 600dpi. Furthermore, the range from 0% to 100% representing the CMYK gradation of each pixel is associated with a range of pixel values ​​from 0 to 255. Alternatively, the print data may be acquired by acquiring a file written in a page description language and performing a rasterization process on the acquired file. In other words, in S401, the CPU 101 may acquire a print job from the image forming apparatus 2.

[0020] In S402, the CPU 101 determines whether or not the acquired print data contains image defect information. Specifically, the defect manifestation area estimation unit 303 determines whether or not image defect information exists for the image forming apparatus 2. This determination is made by acquiring the image defect information held by the image defect information holding unit 302. If image defect information exists for the image forming apparatus 2, the process in S403 is performed; if there is no image defect information for the image forming apparatus 2, the process in S405 is performed. In other words, if image defect information exists, the CPU 101 proceeds from the process in S402 to the process in S403. On the other hand, if there is no image defect information, the CPU 101 proceeds from the process in S402 to the process in S405.

[0021] (Image defect information) Figure 5 shows an example of image defect information used in the S402 process in Figure 4. Image defect information is information indicating an image defect. This information is represented by the shape and color of the image defect. Image defect information is generated by extracting it from images scanned from chart images, etc., that are periodically printed by the image forming apparatus 2. Image defect information is information indicating image defects that may occur when printing with the image forming apparatus 2 in the future. In Figure 5, an example is shown in which the image defect information includes, for each image defect, the identification code of the image forming apparatus 2 where the image defect occurred, the color in which the image defect occurred, the shape and amount of the image defect, the size of the image defect, and information on the main scanning position of the center of the image defect. For example, the identification code of the image forming apparatus 2 is A, and the color in which the defect occurred (hereinafter also referred to as the defective color) is cyan. The size of the defective area is indicated by the size of the bounding box surrounding the defective area (hereinafter appropriately referred to as the defective area). For example, if the shape of the defective area is a narrow rectangle, the size of the bounding box surrounding that rectangle is indicated as 3 mm × 0.5 mm. Furthermore, the location of the defective area is indicated as being at the main scanning position of 5.1 mm. Alternatively, the identification code for the image forming apparatus 2 is A, the defective color is black, the shape of the defective area is a circle, and the size of the bounding box surrounding that circle is indicated as 0.5 mm × 0.5 mm. Furthermore, the location of the defective area is indicated as being at the main scanning position of 140.2 mm. Alternatively, the identification code for the image forming apparatus 2 is B, the defective color is black, the defective shape is a rectangle, and the size of the bounding box surrounding that rectangle is indicated as 100 mm × 3 mm. Furthermore, the location of the defective area is indicated as being at the main scanning position of 140.2 mm. In this embodiment, it is assumed that the identification code for the image forming apparatus 2 is A. In the image forming apparatus 2, yellow, cyan, magenta, and black toner images are formed on the photoreceptor drums 201, 202, 203, and 204, respectively. Information on the color causing the image defect is stored. In this embodiment, information on the shape and amount of the image defect is stored as an 8-bit grayscale image file with a resolution of 600 dpi.

[0022] For colors where image defects occur, each pixel may maintain a range of pixel values ​​from 0 to 255, corresponding to the variation in tonal range from -100% to 100% from the tonal range without image defects. Here, tonal range is represented by the black area ratio in a digital halftone binary pattern necessary to reproduce the same brightness on printed material. Figure 6 shows an example of the digital halftone area ratio necessary to reproduce the desired brightness. In Figure 6, the vertical axis represents brightness, and the horizontal axis represents tonal range. Here, tonal range is represented by the black area ratio in a digital halftone binary pattern necessary to reproduce the same brightness on printed material, as explained above. Tonal range 0% indicates a black area ratio of 0% and an L* value of 99.7, which indicates brightness. On the other hand, tonal range 100% indicates a black area ratio of 100% and an L* value of 0.2, which indicates brightness. In other words, the larger the L* value, the brighter the image and the smaller the black area ratio. On the other hand, the smaller the L* value, the darker the image and the larger the black area ratio. For illustrative purposes, when the black area ratio is 50%, the black area is represented as a square. However, in reality, it is a digital halftone, or halftone dot, which is a collection of dots used to represent shades of gray, with variations in dot size and density.

[0023] Returning to Figure 5, the size of the bounding box is retained as the size of the image defect, as explained above. The bounding box is a rectangle surrounding the defective area. More specifically, the size of the bounding box is represented by the length of the bounding box in the main scanning direction and the length of the bounding box in the sub-scanning direction. In other words, the length of the bounding box in the main scanning direction and the length of the sub-scanning direction surrounding the defective area are retained as information about the shape and amount of the image defect. Here, a defective area is defined as, for example, an area where the absolute value of the gradation variation exceeds 1%. That is, for example, if the absolute value of the difference between the gradation of a certain area and the gradation of the surrounding area exceeds 1%, then that area is considered a defective area. The position of the center of this defective area becomes the main scanning position. In other words, the main scanning position of the defective area is the center position of the bounding box, and is indicated by the distance from the left edge of the printable area to the center position of the bounding box. Furthermore, each image defect may be assigned an ID (identification number). In Figure 5, the IDs for identifying image defects are assigned sequentially from top to bottom as 1, 2, and 3. A detailed example of how to acquire image defect information will be described later. Also, the data storage format for image defect information in Figure 5 is just one example; any format is acceptable as long as it can store the size, color, shape, and quantity of the image defect. For example, the shape of the image defect may be stored as a classification such as streaky or dotted, and other information may also be stored simultaneously.

[0024] Returning to the explanation of Figure 4, in S403, the CPU 101 estimates the defect manifestation areas in the print data. Specifically, the defect manifestation area estimation unit 303 estimates the areas where, if an image defect occurs when the print data is printed using the image forming apparatus 2, the image defect is likely to be noticeable. Figure 7 is a flowchart illustrating a detailed example of the process in S403 of Figure 4. The details of the process in S403 will be explained below using Figure 7. The process shown in Figure 7 is realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The process shown in Figure 7 is executed when the process in S403 of Figure 4 is called. Note that some or all of the functions of the steps in Figure 7 may be realized by hardware such as an ASIC or electronic circuit. The symbol "S" in the explanation of each process means that it is a step in the flowchart. Furthermore, the process shown in Figure 7 can also be realized as a cloud computing configuration in which one function is shared and processed jointly by multiple resources via the internet, as long as it realizes each function of the information processing device 1 in Figure 3.

[0025] In S701, the CPU 101 acquires image defect information. Specifically, the defect manifestation area estimation unit 303 acquires image defect information related to the image forming apparatus 2 from the image defect information holding unit 302. The image defect information related to the image forming apparatus 2 is, for example, the image defect information for the image forming apparatus 2 with identification number A, as shown in Figure 5. In S702, the defect manifestation area estimation unit 303 selects one of the image defect information acquired in the processing of S701 and repeats the processing of S703 to S708. In S703, the CPU 101 determines the search area. Specifically, the defect manifestation area estimation unit 303 determines the selected area in the print data where an image defect may occur as the search area to be searched when estimating whether or not an image defect will manifest. The area where an image defect may occur is a rectangular area, with the image position corresponding to the main scan position of the image defect as the center within the range of the main scan direction, and the width being the pixel range corresponding to the size of the image defect in the main scan direction. The range in the sub-scan direction is the entire pixel range. Hereafter, this area will be called the search area. Note that the width of the search area in the main scan direction may be made wider, for example, it may be the pixel range corresponding to a predetermined constant multiple of the size of the image defect in the main scan direction. The predetermined constant is, for example, 1.5.

[0026] Image defects that may occur in the image forming apparatus 2 are often caused by rotating bodies such as the photoreceptor drums 201, 202, 203, and 204, and the transfer belt 205. When image defects occur in such rotating bodies, they occur at the same main scanning position. Furthermore, unless special control is implemented, such as synchronizing the recording medium transport timing by the transport rollers 207 with the phase of the rotating body, the sub-scan coordinates of the printed image and the phase of the rotating body change with each printing operation. Therefore, it can be said that image defects may occur in the search area described above. By setting the area for estimating whether an image defect will become apparent in this way, it is possible to perform processing at a faster speed compared to estimating the entire image area.

[0027] In S704, the CPU 101 divides the search area. Specifically, the defect manifestation area estimation unit 303 divides the search area along the sub-scanning direction, starting from the side with smaller coordinates in the print data, so that the length of the search area corresponds to a pixel range corresponding to the size of the sub-scanning direction of the image defect. The origin of the coordinates will be described later using Figure 8. Hereafter, this divided area will be called the divided area. The width of the divided area in the sub-scanning direction may be made wider, for example, to a pixel range corresponding to a predetermined constant multiple of the size of the sub-scanning direction of the image defect. The predetermined constant is, for example, 1.5. Figure 8 shows an example of the search area 802 determined by the processing in S703 of Figure 7. Figure 8(a) shows an example of the search area 802 and divided area 803 in the print data. Of the print data 801, the search area 802, which is a rectangular area including the main scan position of the image defect, and the divided area 803, which is a division of the search area 802, are determined by the processing in S703 and S704.

[0028] In S705, the CPU 101 repeats the processes of S706 to S708 for each divided region 803 created in the process of S704. Specifically, the defect manifestation area estimation unit 303 scans each divided region 803 created in the process of S704 one by one and repeats the processes of S706 to S708. In S706, the CPU 101 calculates an evaluation value used to determine whether or not an image defect is manifested. Specifically, the defect manifestation area estimation unit 303 estimates how noticeable an image defect is when it occurs in the center of the divided region 803 and calculates it as an evaluation value. Figure 9 is a diagram showing an example of an image pattern in which an image defect is manifested. Before explaining the details of the evaluation value calculation process, we will explain the image pattern in which a defect is manifested using Figure 9.

[0029] The first image pattern is text and lines. Figure 9(a) shows a case where an image defect occurs on text. Compared to other graphics, users tend to focus on text and lines more often, and image defects are more easily noticeable. Therefore, for example, if an image defect such as an image defect 905, where there is insufficient toner, occurs in the text image pattern 901, it is determined that the image defect is apparent. The evaluation value for this determination is calculated in the processing S1001 to S1003 described later.

[0030] The second image pattern involves a large color difference between the defective area and the image area. Figure 9(b) shows a case where an image defect occurs in a high-density area of ​​the image due to insufficient toner. Image defects are often perceived as color differences, and color differences in adjacent areas tend to be more easily perceived than color differences in separated areas. Therefore, for example, if an image defect such as an image defect 905, where there is insufficient toner in a high-density image pattern 902, occurs, it is determined that the image defect is manifest. The evaluation value for this determination is calculated in the processing S1004 to S1011 described later.

[0031] A third image pattern is one in which the high-frequency components are fewer compared to the spatial frequency of the image defect. Figures 9(c) to 9(f) show the results when the spatial frequency of the image defect and the spatial frequency of the image pattern are varied, respectively. For the low-frequency image pattern 903, the image defect is conspicuously perceived in both the case where the high-frequency image defect 906 is present (Figure 9(c)) and the case where the low-frequency image defect 907 is present (Figure 9(e)). On the other hand, for the high-frequency image pattern 904, the image defect is conspicuous when the high-frequency image defect 906 is present (Figure 9(d)). However, when the low-frequency image defect 907 is present in relation to the high-frequency image pattern 904 (Figure 9(f)), the low-frequency image defect 907 is concealed by the high-frequency image pattern 904. Therefore, it is determined that the image defect becomes apparent when the image pattern has fewer high-frequency components compared to the spatial frequency of the image defect. The evaluation value for this determination is calculated in the processing S1012 to S1016 described later. In S706, the evaluation value is calculated by checking whether the image pattern is one of the three image patterns described above. This concludes the explanation of Figure 9.

[0032] Figure 10 is a flowchart illustrating a detailed example of the process S706 in Figure 7. The details of the process S706 will be explained using Figure 10. The process shown in Figure 10 is realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The process shown in Figure 10 is executed when the process S706 in Figure 7 is called. Note that some or all of the functions of the steps in Figure 10 may be realized by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process means that it is a step in the flowchart. Furthermore, the process shown in Figure 10 can also be realized as a cloud computing configuration in which one function is shared and processed jointly by multiple resources via the internet, as long as it realizes each function of the information processing device 1 in Figure 3.

[0033] (Evaluation based on text and lines) In S1001, CPUI01 acquires the positions of characters and lines. Specifically, the defect manifestation area estimation unit 303 acquires the character and line areas in the divided area 803 of the print image data as the character and line positions. Hereafter, the print data in the divided area 803 will be referred to as the divided area image. A known optical character recognition method may be used for acquisition. If the print data acquired in S401 was generated from a page description language, the character and line areas may also be acquired from the information described in the page description language. The acquired character and line area information can be stored, for example, as a 1-bit 2D array of the same size as the divided area image, with 1 representing character and line areas and 0 representing non-character and line areas.

[0034] In S1002, the CPU 101 determines whether the image defect overlaps with characters or lines. Specifically, the defect manifestation area estimation unit 303 determines whether the image defect at the center of the divided area 803 overlaps with the area of ​​characters or lines in the print data. If there is an overlap, it proceeds to processing S1003; otherwise, it proceeds to processing S1004. As an example of the determination method, a 1-bit 2D array is generated, where 1 is used for pixels with image defects and 0 for pixels without image defects. Image defects are determined, for example, by checking whether the pixel value of each pixel is 127, which is the pixel value when there is no image defect. Here, for each pixel, the range of tonal variation from -100% to 100% from the tonal variation when there is no image defect is associated with the range of pixel values ​​from 0 to 255. Therefore, a tonal variation of 0% corresponds to the pixel value of 127 when there is no image defect. Furthermore, the generated two-dimensional array and the two-dimensional array representing the character and line area information obtained in the S1001 process are logically combined, and a determination is made based on whether or not an element with a value of 1 exists. In S1003, the CPU 101 sets an evaluation value. Specifically, the defect manifestation area estimation unit 303 sets the evaluation value to 10 and terminates the process.

[0035] (Evaluation value based on color difference) In S1004, the CPU 101 converts the divided region image into grayscale values. Specifically, the defect manifestation area estimation unit 303 converts the pixel values ​​of the divided region image into a three-dimensional array I(i,j,k) which has floating-point values ​​from 0% to 100% representing the grayscale at each pixel value for each CMYK color of the image data. The subscripts i and j represent the position coordinates in the main scanning direction and sub-scanning direction, respectively, and the subscript k represents the color. In S1005, the CPU 101 converts the shape and amount of image defects into grayscale values. Specifically, the defect manifestation area estimation unit 303 converts each pixel value of the image representing the shape and amount of image defects into a two-dimensional array D(i,j) which has floating-point values ​​from -100% to 100% representing the grayscale variation. In S1006, the CPU 101 calculates an image J by superimposing the image defects onto the divided region image. Specifically, the defect manifestation area estimation unit 303 creates an image J(i,j,k) by superimposing the image defect onto the divided area image. More specifically, it creates a two-dimensional array J(i,j,k) of grayscale values ​​where the color of the image defect is added to the color of the image defect, and the same as the divided area image for colors other than the color of the image defect. In other words, if the color of the image defect is c, J(i,j,k) can be expressed as shown in Equation 1.

[0036]

number

[0037] In S1007, the CPU 101 blurs the superimposed image J with respect to the color of the image defect. Specifically, the defect manifestation area estimation unit 303 blurs the color component J(i,j,k=c) of the image defect in the superimposed image. This blurring process is intended to reflect the effect of toner, which is an image forming material, scattering around the printing position in the calculation of the color difference in S1010, which will be described later. A Gaussian filter blurring process is applied to the superimposed image J(i,j,k=c) with respect to the color of the image defect. The standard deviation of the Gaussian filter is calculated by determining the average gradation value E of the divided area image I(i,j,k=c) with respect to the color of the image defect, for example, 0.1mm × E.

[0038] In S1008, the CPU 101 blurs the superimposed image J for all colors. Specifically, the defect manifestation area estimation unit 303 blurs all color components J(i,j,k) of the superimposed image created in S1007. This blurring process is to reflect the light diffusion effect (optical dot gain) of the printing medium caused by the toner image in the calculation of the color difference in S1010, which will be described later. To determine the half-width of the Gaussian filter, which is a parameter of the blurring process, first, the average gradation value E(k) is calculated for each color component of the divided region image I(i,j,k). The average gradation value E(k) for each color component is converted to a brightness value F by color conversion. For this conversion, a table T is created in advance, which shows the correspondence between each CMYK gradation and each value in the CIEL*a*b* color space that represents how the gradation looks when printed by an image forming apparatus, and the brightness value F is obtained as the L* value obtained by the conversion using table T. Using the acquired brightness value F, for example, the full width at half maximum of a Gaussian filter is set to 0.1 mm × (100-F) / 100, and blurring is performed on all color components J(i,j,k) of the superimposed image. Figure 11 is a schematic diagram showing the effect of toner scattering around the printing position and the light diffusion effect of the toner image on the printing medium. Figure 11(a) shows the state in which image defect 1103 occurs in image 1101 with 30% grayscale. Figure 11(b) shows the state in which the same image defect 1103 as in Figure 11(a) occurs in image 1102 with 90% grayscale. The effect of toner scattering from areas of the image to areas of the image and the light diffusion effect of the toner image on the printing medium become more pronounced at higher grayscale levels. Therefore, the image defect 1103 in Figure 11(b) appears smaller in shape and the density difference between the image area and the non-image area is also reduced compared to the image defect 1103 in Figure 11(a). The processing in S1007 and S1008 reflects the effect of toner scattering around the printing position and the light diffusion effect of the toner image on the printing medium, which has the effect of determining whether the image defect will manifest in a state closer to what it actually looks like. In S1009, the CPU 101 performs a color conversion on the divided region image and the superimposed image J. Specifically, the defect manifestation area estimation unit 303 performs a color conversion on the divided region image I(i,j,k) and the superimposed image J(i,j,k).In S1007, L*, a*, and b* values ​​are obtained for each pixel by the conversion using table T. The three-dimensional arrays obtained by color-converting the divided region image I(i,j,k) and the superimposed image J(i,j,k) are denoted as I′J′(i,j,m), respectively. Here, the subscript m represents one of the components of L*, a*, or b*. In S1010, the CPU 101 calculates the color difference between the divided region image and the superimposed image J. Specifically, the defect manifestation area estimation unit 303 calculates the color difference for each pixel of the color-converted divided region image I′(i,j,m) and the superimposed image J′(i,j,m), and calculates the maximum value H. This obtains the color difference between cases where an image defect occurs in the divided region image and cases where it does not. In this embodiment, the maximum color difference H is obtained by equation 2.

[0039]

number

[0040] In S1011, the CPU 101 sets the maximum color difference H as the evaluation value. Specifically, the defect manifestation area estimation unit 303 sets the maximum color difference H as the evaluation value.

[0041] (Evaluation value based on frequency) In S1012, the CPU 101 performs frequency transformation on the shape and amount of image defects. Specifically, the defect manifestation area estimation unit 303 performs a Fourier transform on the image D(i,j) representing the shape and amount of image defects to obtain the frequency image d(u,v) after the Fourier transform. The subscripts u and v represent the frequency coordinates with respect to the main scanning direction and the sub-scanning direction, respectively. In S1013, the CPU 101 calculates the high-frequency feature quantity Λ of the image defect. Specifically, the defect manifestation area estimation unit 303 calculates feature quantities Λu and Λv that represent the high-frequency components included in the image defect. Specifically, it calculates Λu and Λv that satisfy the following equations 3 and 4.

[0042]

number

[0043]

number

[0044] In S1014, the CPU 101 performs frequency transformation on the divided region image. Specifically, the defect manifestation region estimation unit 303 performs a Fourier transform on the brightness value I′(i,j,m=L*) of the divided region image after color transformation to obtain the frequency image i′(u,v) after the Fourier transform. In S1015, the CPU 101 calculates the proportion r in the divided region image that has a frequency higher than Λ. Specifically, the defect manifestation region estimation unit 303 calculates the proportion r in the divided region image that has a frequency higher than the high-frequency components Λu and Λv included in the image defects. More specifically, it is calculated by the following equation 5.

[0045]

number

[0046] Here, max(a,b) is a function that returns the larger of a and b. In S1016, the CPU 101 calculates an evaluation value by multiplying the evaluation value calculated in S1011 by (1-r). Specifically, the defect manifestation area estimation unit 303 calculates an evaluation value by multiplying the evaluation value calculated in S1011 by (1-r) based on the ratio r. This concludes the explanation of Figure 10.

[0047] Returning to Figure 7, in S707, the CPU 101 determines whether the evaluation value is greater than the threshold ThE. Specifically, the defect manifestation area estimation unit 303 determines whether the evaluation value obtained in S706 is greater than the threshold ThE, and if it is, it performs the process in S708. The threshold ThE is, for example, 25. In S708, the CPU 101 determines the divided region to be a defect manifestation area and terminates the process. Specifically, the defect manifestation area estimation unit 303 determines the selected divided region to be a defect manifestation area and terminates the process. This concludes the explanation of Figure 7.

[0048] Figure 8(b) shows an example of the estimation results for the defect manifestation area. The print data 801 displays the search areas 802 and 804 related to two image defects occurring in the image forming apparatus 2, and the defect manifestation area 805 superimposed on it. In this example, the image defect corresponding to the search area 802 is an image defect where the black toner is insufficient, and there is an area where the color difference between the non-defective and defective areas is large in the part that overlaps with the character line area. Furthermore, there is an area where there are few image components with a frequency higher than the frequency of the image defect. As a result of considering these areas, the defect manifestation area 805 is determined. On the other hand, the image defect corresponding to the search area 804 is an image defect where the cyan toner is slightly excessive, and there is no area determined to be a defect manifestation area.

[0049] Returning to Figure 4, in S404, the CPU 101 determines whether or not printing is possible. Specifically, the print execution determination unit 304 determines whether or not to execute printing based on the defect manifestation area estimated in S403. For each image defect that may occur in the image forming apparatus 2, the determination is made by calculating the ratio Kn of the area of ​​the search area and the area of ​​the defect manifestation area. The subscript n represents the type of image defect. Except in the special case where the printing period matches an integer multiple of the period of the rotating member in the image forming apparatus 2, it is considered that the appearance of image defects caused by the rotating member at any sub-scan position in the printed image is uniformly random. Therefore, Kn is the probability that the image defect will appear at the position where the defect manifests, and corresponds to the proportion of the number of printed sheets with noticeable image defects out of the total number of printed sheets. By making a determination whether or not to execute printing based on this ratio Kn, an appropriate print instruction can be given. In this embodiment, if the ratio Kall obtained by the following equation 6 is greater than the threshold ThR, it is determined to execute printing and the process in S404 is executed; otherwise, it is determined not to execute printing. Let's assume the threshold ThR is 0.1, for example.

[0050]

number

[0051] Here, the summation symbol means that the sum is taken for all possible image defects that may occur in the image forming apparatus 2. In S405, the CPU 101 executes the print job and then proceeds to the process in S406. Specifically, the print instruction unit 305 instructs the image forming apparatus 2 to execute the print job and perform image formation on the print image data. In S406, the CPU 101 displays the print instruction result. Specifically, the print instruction result display unit 306 displays information on the display 104 of the information processing device 1 indicating whether or not printing has been performed. Figure 12 is a diagram showing an example of the notification screen displayed in the process of S406 in Figure 4. A notification window 1201 displayed on the display 104 contains a notification message 1202 and a button 1203. If the notification message 1202 determines that printing will be performed, it will display, for example, "Printing is in progress," indicating that printing will be performed. If printing will not be performed, it will display, for example, "Printing has been stopped because an image defect is expected to occur. Please perform maintenance or try printing another image," indicating that printing has been stopped. Button 1203 is positioned to close the notification window 1201. The user closes the notification window 1201 by pressing button 1203 via the operation unit 105. This concludes the explanation of the processing performed by the information processing device 1.

[0052] Finally, an example of the process for creating image defect information held in the image defect information holding unit 302 will be described. Figure 13 is a diagram showing an example of the functional configuration of the information processing device 1 in Figure 1 when the process for acquiring image defect information is executed. Note that in Figure 13, in addition to the information processing device 1 and the image forming apparatus 2, an image reading device 11 has been newly added. The image reading device 11 is provided, for example, on the downstream side of the image forming apparatus 2 and is capable of reading images recorded on the recording medium by the image forming apparatus 2 inline. The information processing device 1 further comprises a chart printing instruction unit 1201, a reference image holding unit 1202, and an image defect analysis unit 1203. The chart printing instruction unit 1201 instructs the image forming apparatus 2 to print a chart. The image defect analysis unit 1203 analyzes image defects by comparing the data read by the image reading device 11 with the reference image held in the reference image holding unit 1202. Furthermore, the image defect analysis unit 1203 stores the information obtained from analyzing the image defects in the image defect information storage unit 302. However, the processing may also be performed by an information processing device other than the information processing device 1, which has the same functional configuration.

[0053] Figure 14 is a flowchart illustrating a detailed example of the process for acquiring image defect information. The process shown in Figure 14 is implemented by the CPU 101 executing a program stored in RAM 103 or ROM 102. The process shown in Figure 14 is executed when instructions are received from the user via the operation unit 105 in Figure 1. Note that some or all of the functions of the steps in Figure 14 may be implemented by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process means that it is a step in the flowchart. Furthermore, the process shown in Figure 14 can also be implemented as a cloud computing configuration in which a single function is shared and processed collaboratively by multiple resources via the internet, as long as it implements each function of the information processing device 1 in Figure 13.

[0054] In S1401, the CPU 101 initiates chart printing. Specifically, the chart printing instruction unit 1201 instructs the image forming apparatus 2 to print four A3-sized images with uniform 25% gradation for each CMYK color as chart images. Chart printing instructions are given, for example, at predetermined time intervals. The image reading device 11 reads the print results from the image forming apparatus 2 and transmits the read images to the information processing device 1. The read images are, for example, 8-bit RGB image files with a resolution of 600 dpi. The predetermined time intervals are, for example, every 3000 prints or every day. Alternatively, they may be done between jobs.

[0055] In S1402, the CPU 101 calculates the difference between the reference image and the read image. Specifically, the image defect analysis unit 1203 calculates the difference between the reference image, which is a read image of a chart printed by an image forming apparatus that does not produce image defects and is held in the reference image holding unit 1202, and the read image. To calculate the difference, the reference image and the read image are first aligned. As an alignment method, for example, markers are set in advance at the four corners of the chart and the template matching method is used. Subsequently, a difference image is obtained by taking the difference between pixels at the same position in each image.

[0056] In S1403, the CPU 101 classifies image defects. Specifically, the image defect analysis unit 1203 classifies image defects from the difference image. More specifically, the image defect analysis unit 1203 converts the difference image to grayscale, performs a binarization process to separate the defective parts from the non-defective parts, and classifies the image defects through a labeling process.

[0057] In S1404, the CPU 101 acquires image defect information. Specifically, the image defect analysis unit 1203 acquires information on the color, main scan position, shape, and quantity of each classified image defect. For the color of the image defect, it acquires which CMYK color chart it occurred in. The main scan position of the image defect is calculated from the image coordinates. The shape and quantity of the image defect are acquired by converting the difference image after grayscale conversion to the amount of gradation change from the gradation when there is no defect, using a pre-created table representing the relationship between brightness values ​​and gradation.

[0058] In S1405, the CPU 101 stores image defect information. Specifically, the image defect analysis unit 1203 stores the information of each image defect acquired in S1404 in the image defect information storage unit 302. If an image defect with the same main scan position and defective color already exists in the image defect information storage unit 302, it may be determined that the image defect is the same as the image defect obtained in this flowchart. In that case, the image defect information already existing in the image defect information storage unit 302 is updated and stored.

[0059] This concludes the explanation of the process for creating image defect information. Note that the described method for obtaining image defect information is merely an example; other methods may be used to obtain the color, shape, quantity, size, and main scanning position of the defects to be retained as image defect information. For example, image defects could be extracted by scanning a printed output produced by the user, or the occurrence of image defects could be predicted from sensors installed in various parts of the printing image forming apparatus. Furthermore, if maintenance is performed on the image forming apparatus 2 and it is determined that the image defects retained as image defect information will not appear again, the image defect information related to that image forming apparatus may be deleted. By performing the process control described above, it is possible to estimate whether image defects will become apparent considering the printed image data and to automatically issue print instructions based on the estimation result, thereby preventing a decrease in production efficiency.

[0060] Furthermore, the information processing device 1 may further include a first threshold changing unit, allowing the threshold ThR in S404 to be changed. For example, it may be changed by user instruction. As mentioned above, the value compared with the threshold ThR is related to the proportion of pages with noticeable image defects out of the total number of printed pages. Therefore, by allowing the threshold ThR to be changed by user instruction, it is possible to provide more accurate print instructions that reflect how much of a proportion of pages with noticeable image defects the user is willing to accept.

[0061] Furthermore, the information processing device 1 may also be equipped with a second threshold changing unit, allowing the threshold ThE in S607 to be changed. For example, it may be changed by receiving instructions from the user via the operation unit 105. This makes it possible to perform a more accurate estimation of image defect manifestation that reflects the user's tolerance for the degree to which image defects become apparent.

[0062] Furthermore, the setting of evaluation values ​​in S1003, S1011, and S1016 is merely an example. The specific values ​​may differ from those in this embodiment, as long as the evaluation values ​​are set to be high in cases such as when the defect overlaps with a character or line area, when there is a large color difference between the defective and non-defective areas, or when there are fewer high-frequency image frequencies compared to the image frequencies of the defective area.

[0063] (Second embodiment) In the first embodiment, a method was described for the information processing device 1 to automatically determine whether to perform printing. In this embodiment, an example is described in which the user is presented with an image of what will appear when a defect occurs, and the user decides whether to perform printing. Note that the explanation will focus on the differences from the above-described embodiment, and similar points will be omitted.

[0064] The hardware configuration of the information processing device 1 described in this embodiment is the same as that of Embodiment 1, so its description will be omitted. Figure 15 is a diagram showing an example of the functional configuration of the information processing device in the second embodiment. Functions identical to those in the first embodiment are denoted by the same reference numerals, and the description of functions denoted by the same reference numerals as those in the first embodiment will be omitted. As shown in Figure 15, the information processing device 1 further includes a simulated defective image presentation unit 307 and a defective manifestation area estimation unit 303. The simulated defective image presentation unit 307 and the defective manifestation area estimation unit 303 are also functions realized by the CPU 101 of the information processing device 1 executing a program stored in the RAM 103 or the like. The simulated defective image presentation unit 307 includes the function of generating a simulated defective image that simulates how an image defect would look if one occurred in the defective manifestation area estimated by the defective manifestation area estimation unit 303, and presenting it to the user by displaying it on the display 104. The print execution decision unit 308 includes a function to acquire, via the operation unit 105, the user's decision to execute printing after confirming the image presented by the simulated defective image presentation unit 307.

[0065] Figure 16 is a flowchart illustrating the processes executed in the functional configuration of the information processing device 1 shown in Figure 15. The details of the processes executed by the information processing device 1 will be explained below using Figure 15. Note that the number of steps identical to those in Figure 4 are the same as in the first embodiment, and therefore their explanation will be omitted. The processes shown in Figure 16 are realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The processes shown in Figure 16 are executed when instructions are received from the user via the operation unit 105 in Figure 1. Note that some or all of the functions of the steps in Figure 16 may be implemented by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process indicates a step in the flowchart. Furthermore, the processes shown in Figure 16 can also be implemented as a cloud computing configuration where a single function is shared and processed collaboratively by multiple resources via the internet, as long as they realize each function of the information processing device 1 in Figure 15.

[0066] In S1604, the CPU 101 determines whether or not there is a defect manifestation area. Specifically, the print execution determination unit 308 determines whether or not there is a defect manifestation area estimated by the defect manifestation area estimation unit 303. If it does not exist, it performs the process in S405 to execute printing. On the other hand, if it does exist, it performs the process in S1605.

[0067] In S1605, the CPU 101 presents an image of the defect. Specifically, the simulated defect image presentation unit 307 generates a simulated defect image that simulates how the image would look if a defect occurred in the defect manifestation area estimated by the defect manifestation area estimation unit 303, and presents it to the user by displaying it on the display 104. Figure 17 is a flowchart illustrating a detailed example of the process in S1605 of Figure 16. The details of the process will be explained below using Figure 17. The process shown in Figure 17 is realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The process shown in Figure 17 is executed when the process in S1605 of Figure 16 is called. Note that some or all of the functions of the steps in Figure 17 may be realized by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process means that it is a step in the flowchart. Furthermore, the processes shown in Figure 17, if they implement the respective functions of the information processing device 1 in Figure 15, can also be implemented as a cloud computing configuration in which a single function is shared and processed collaboratively by multiple resources via the internet.

[0068] In S1701, the CPU 101 selects a divided region that is a defect manifestation area. Specifically, the simulated defect image presentation unit 307 selects one of the divided regions estimated to be a defect manifestation area. In S1702, the CPU 101 converts the print data into grayscale values. Specifically, the simulated defect image presentation unit 307 converts the print data into grayscale values. This process is the same as the process performed by the defect manifestation area estimation unit 303 on the divided region image in S1004, so the explanation is omitted. In S1703, the CPU 101 converts the shape and amount of image defects into grayscale values. Specifically, the simulated defect image presentation unit 307 converts the shape and amount of image defects into grayscale values. This process is the same as the process performed by the defect manifestation area estimation unit 303 in S1004, so the explanation is omitted. In S1704, the CPU 101 extracts the divided region from the print data. Specifically, the simulated defective image presentation unit 307 extracts the portion of the print data corresponding to the divided region selected in S1701. The processing performed by the CPU 101 in S1705 to S1707 is the same as the processing performed by the CPU 101 in S1006 to S1008. That is, the processing performed by the simulated defective image presentation unit 307 using the divided region image extracted in S1704 is the same as the processing performed by the defect manifestation region estimation unit 303 in S1006 to S1008, so the explanation is omitted. In S1708, the CPU 101 replaces a portion of the print data with a superimposed image and places it. Specifically, the simulated defective image presentation unit 307 replaces the portion of the print data corresponding to the divided region with the superimposed image created in S1707 and places it. In S1709, the CPU 101 performs a color conversion on the print data. Specifically, the simulated defective image presentation unit 307 converts the print data, which is an image holding CMYK gradation values, into an image with RGB signal values ​​for display on the display 104 of the information processing device 1. The color conversion can be performed by conversion using a known color profile. In S1710, the CPU 101 presents the image and terminates the process. Specifically, the simulated defective image presentation unit 307 displays a UI (User Interface) on the display 104 of the information processing device 1, which includes print data with the image defects calculated in S1709 superimposed.Figure 18 shows an example of the UI displayed in the S1710 process in Figure 17. Inside window 1801, print data 1802 with the image defect superimposed and an enlarged image 1803 showing the image defect enlarged are displayed. Furthermore, a message 1804 is displayed asking the user whether or not to accept the image defect, and buttons 1805 to be pressed if the user accepts it and 1806 to be pressed if the user does not accept it are displayed. This concludes the detailed explanation of the S1604 process using Figure 17, and we return to the explanation of Figure 16. In S1605, the CPU 101 presents an image of the defect and accepts user input. Specifically, the print execution decision unit 308 obtains the user's decision to execute print after viewing the image presented by the simulated defect image presentation unit 307, via the operation unit 105. When button 1805 in Figure 18 is pressed, it is determined to execute print and the process in S405 is performed, and when button 1806 is pressed, it is determined not to execute print and the process in S406 is performed. By performing the processing control described above, according to the second embodiment, the user can check how the image will look in areas where image defects are noticeable for each print data, and then decide whether to proceed with printing, thereby enabling more accurate print instructions.

[0069] (Third embodiment) In the first embodiment, an information processing device 1 connected to one image forming apparatus 2 was described. In this embodiment, an information processing device 1 connected to multiple image forming apparatuses 2A, 2B will be described. In this embodiment, the information processing device 1 estimates the likelihood of image defects becoming apparent for each image forming apparatus 2 and issues a print instruction to the image forming apparatus in which no image defects are apparent. Note that this description will focus on the differences from the above-described embodiment, and similar points will be omitted.

[0070] The hardware configuration of the information processing device described in this embodiment differs from the hardware configuration of the information processing device in Embodiment 1 in that the information processing device 1 is connected to multiple image forming apparatuses 2A and 2B via a network. Figure 19 shows an example of the functional configuration of the information processing device 1 in the third embodiment. The defect manifestation area estimation unit 303 estimates whether or not image defects will manifest in each of the image forming apparatuses 2A and 2B. The print execution determination unit 304 determines whether to execute printing in each of the image forming apparatuses 2A and 2B, and the print instruction unit 305 issues a print instruction to either the image forming apparatus 2 or the image forming apparatus 3 based on the print execution determination of the print execution determination unit 304.

[0071] Figure 20 is a flowchart illustrating the processes performed by the information processing device 1 with the functional configuration shown in Figure 19. The explanation will focus on the differences from the first embodiment. In S2001, the CPU 101 performs the processes S402 to S404 for each image forming apparatus. Specifically, the defect manifestation area estimation unit 303 and the print execution determination unit 304 assign ID numbers to the image forming apparatuses 2A and 2B connected to the information processing device 1, and select them in ascending order of ID number. In the subsequent loop, the process estimates the defect manifestation area and makes a decision on whether to execute printing for image defects occurring in the selected image forming apparatus. In S404, if the print execution determination unit 304 decides to execute printing, it exits the loop, and in S405, the print instruction unit 305 issues a print instruction to the selected image forming apparatus. In S406, the print instruction result display unit 306 displays information on the display 104 of the information processing device 1 indicating whether printing was performed and which image forming apparatus will be used for printing. An example of the information to be displayed is shown in Figure 21. Figure 21 shows an example of a notification screen displayed during the S406 process in Figure 20. Window 2101 contains text 2102 indicating the image forming apparatus that performs printing, and a button 2103 for the user to close window 2101.

[0072] By performing the processing control described above, according to the third embodiment, it is possible to automatically select an image forming apparatus that does not produce noticeable image defects for each print data and perform printing. Therefore, while maintaining print quality, it is possible to issue print instructions to image forming apparatuses that do produce image defects, depending on the print image data, thereby improving overall productivity.

[0073] In this embodiment, the case where the information processing device 1 is connected to two image forming machines has been described, but it may be connected to three or more image forming machines. Furthermore, regarding the order in which IDs are assigned to image forming machines, smaller IDs may be assigned in order from the image forming machine with the most image defect information. In this case, if there are multiple image forming machines where image defects are not apparent, a print command can be issued to the image forming machine with the most image defect information among them. This allows for priority printing of image forming machines that have a low utilization rate due to a small variety of printable image data caused by a large amount of image defect information, thereby leveling the utilization rate of the image forming machines and improving overall printing efficiency. Alternatively, smaller IDs may be assigned in order from the image forming machine with the lowest printing cost per sheet. In this case, if there are multiple image forming machines where image defects are not apparent, a print command can be issued to the image forming machine with the lowest printing cost among them. This reduces printing costs. Additionally, smaller ID numbers may be assigned in order from the image forming machine with the fewest print jobs held at the time of processing. In that case, if there are multiple image forming machines where image defects do not become apparent, a print command can be issued to the image forming machine with the fewest print jobs currently running. This allows for leveling out the operating rates of the image forming machines and thereby improving overall printing efficiency. It is also possible to implement the present invention in an image forming system consisting of an information processing device and multiple image forming machines connected to the information processing device.

[0074] (Fourth embodiment) In the first to third embodiments, the system estimated whether the image data to be printed next had noticeable image defects and made a decision on whether to proceed with printing. However, even if the image data to be printed next has noticeable image defects and cannot be printed, other jobs fed into the information processing device may contain printable image data. This embodiment describes an example in which the system checks all of the multiple print jobs fed into the information processing device and performs printing on the print jobs that contain printable image data. The following mainly describes the differences between this embodiment and the first, second, and third embodiments.

[0075] <Functional configuration of information processing device 1> Figure 22 is a diagram showing an example of the functional configuration of the information processing device in the fourth embodiment. The functional configuration of the information processing device 1 will be described below using Figure 22. The information processing device 1 includes a print job data acquisition unit 2201, an image defect information storage unit 302, a defect manifestation area estimation unit 2203, a print job selection unit 2204, a print job print instruction unit 2205, and a print instruction result display unit 2206. The print job data acquisition unit 2201 acquires image data for all jobs to be printed by the image forming apparatus 2 from the HDD 106 or a recording medium on the Internet. The image defect information storage unit 302 is the same as in the first embodiment, so its description will be omitted. The defect manifestation area estimation unit 2203 estimates the image areas in the image data of the print jobs acquired by the print job data acquisition unit 2201 in which image defects are noticeable during printing. The estimation is performed based on the image data and image defect information acquired from the image defect information storage unit 302. The print job selection unit 2204 selects a print job to be printed based on the area estimated by the defect area estimation unit 2203. The print job print instruction unit 2205 instructs the image forming apparatus 2 to print the image data of the print job selected by the print job selection unit 2204. The print instruction result display unit 2206 displays the print instruction result from the print job print instruction unit 2205 on the display 104.

[0076] <Processing by Information Processing Device 1> Figure 23 is a flowchart illustrating the processes executed in the functional configuration of the information processing device shown in Figure 22. The processes of the information processing device 1 will be described below using Figure 23. The processes shown in Figure 23 are realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The processes shown in Figure 23 are executed when instructions are received from the user via the operation unit 105 in Figure 1. Note that some or all of the functions of the steps in Figure 23 may be implemented by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process indicates a step in the flowchart. Furthermore, the processes shown in Figure 23 can also be implemented as a cloud computing configuration where a single function is shared and processed collaboratively by multiple resources via the internet, as long as they realize each function of the information processing device 1 in Figure 22.

[0077] In S2301, CPUI01 acquires print job data. Specifically, the print job data acquisition unit 2201 acquires image data for all jobs to be printed by the image forming apparatus 2 from a recording medium on the internet or the like. In S2302, CPU101 determines whether or not there is image defect information. Specifically, the defect manifestation area estimation unit 2203 refers to the information in the image defect information holding unit 302 and determines whether or not image defect information exists for the image forming apparatus 2. If there is no image defect information for the image forming apparatus 2, S2303 is executed; if there is image defect information, processing from S2304 onwards is executed. In S2303, CPU101 selects all print jobs. Specifically, the print job selection unit 2104 selects all print jobs acquired in S2301. In S2304, CPU101 estimates the defect manifestation area of ​​the image data for each print job. Specifically, the defect manifestation area estimation unit 2103 estimates areas where image defects are likely to be noticeable when the image data acquired in S2301 is printed by the image forming apparatus 2. More specifically, area estimation is performed by applying the processing in S403 of the information processing apparatus 1 in the first embodiment to each image data. In S2305, the CPU 101 selects a job to print. Specifically, the print job selection unit 2204 selects a job to print based on the defect manifestation area estimated in S2304. More specifically, for each image data, it calculates Kall based on S404 of the information processing apparatus 1 in the first embodiment and selects a print job with image data greater than the threshold ThR. In S2306, the CPU 101 executes the selected print job. Specifically, the print job print instruction unit 2205 instructs the image forming apparatus 2 to execute the print job selected in S2303 or S2305. In S2307, the CPU 101 displays the print instruction result. Specifically, the print instruction result display unit 2206 displays the print instruction result for the image forming apparatus 2 on the display 104 of the information processing device 1. Similar to the first embodiment, a notification message is displayed in the notification window 1201 shown in Figure 12.Notification messages may include, for example, "Printing: <File name of the print job selected for printing>" and "Printing on hold: <File name of the print job not selected for printing>".

[0078] <Effects of the fourth embodiment> With this embodiment, even if printing is not possible due to an image defect in the next print job, the downtime of the image forming apparatus can be reduced by printing another printable job.

[0079] (Fifth embodiment) In the fourth embodiment, the selection of a print job was made based on the image data of the print job. However, the user may have assigned an image quality to a print job, and it is also possible to select whether or not to print accordingly. This embodiment describes an example of selecting a print job according to the image quality set for the print job. The following mainly describes the differences between this embodiment and the fourth embodiment.

[0080] <Functional configuration of information processing device 1> Figure 24 is a diagram showing an example of the functional configuration of the information processing device in the fifth embodiment. The functional configuration of the information processing device 1 will be described below using Figure 24. The information processing device 1 includes a print job data acquisition unit 2401, an image defect information holding unit 302, a defect manifestation area estimation unit 2402, a print job selection unit 2204, a print job print instruction unit 2205, and a print instruction result display unit 2206. The print job data acquisition unit 2401 acquires image data for all jobs to be printed by the image forming apparatus 2 from the HDD 106 or a recording medium on the internet. Each image data is also assumed to be associated with image quality information. The image quality information sets the image quality level for the print job in the range of 1 to 5 (the higher the number, the better the image quality). This value may be changed to another range, or it may be set using words other than numbers, such as "good," "average," or "bad." The image quality information may be set by the user, or it may be set automatically based on the type of image data for the print job (photograph, document, text, etc.). The image defect information holding unit 302 is the same as in the first embodiment and will therefore be omitted. The defect manifestation area estimation unit 2402 estimates the image areas in the print job image data acquired by the print job data acquisition unit 2401 where image defects during printing are noticeable. The estimation is performed based on the image data, image defect information acquired from the image defect information holding unit 302, and the image quality level of the print job. The print job selection unit 2204, the print job print instruction unit 2205, and the print instruction result display unit 2206 are the same as in the fourth embodiment, so their descriptions are omitted.

[0081] <Processing by Information Processing Device 1> Figure 25 is a flowchart illustrating the processes performed by the information processing device in the functional configuration of Figure 24. The processes of the information processing device 1 will be described below using Figure 25. The processes shown in Figure 25 are realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The processes shown in Figure 25 are executed when instructions are received from the user via the operation unit 105 in Figure 1. Some or all of the functions of the steps in Figure 25 may be realized by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process means that it is a step in the flowchart. Furthermore, the processes shown in Figure 25 can also be realized as a cloud computing configuration in which one function is shared and processed jointly by multiple resources via the internet, as long as they realize each function of the information processing device 1 in Figure 24. S2301, S2302, and S2303 are the same as in the fourth embodiment, so their descriptions are omitted. In S2501, the CPU 101 estimates the area where defects are apparent in the image data for each print job. Specifically, the defect manifestation area estimation unit 2402 estimates areas where image defects are likely to be noticeable when the image data acquired in S2301 is printed by the image forming apparatus 2. Specifically, area estimation is performed by applying the processing in S403 of the information processing apparatus 1 in the first embodiment to each image data. Furthermore, the threshold value ThE set in the processing in S607 of the information processing apparatus 1 is changed based on the image quality set for the print job. For example, when the image quality level is 1 (lowest level), ThE is set to 0, and when the image quality level is 5 (highest level), ThE is set to 30, etc. Since S2305, S2306, and S2307 are the same as in the fourth embodiment, their explanations are omitted.

[0082] <Effects of Example 5> With this embodiment, by using the image quality set for the print job, it becomes possible to perform printing even for print jobs where image defects are expected to be noticeable, if the image quality of the printed image is not a concern. This reduces the downtime of the image forming apparatus.

[0083] (Sixth embodiment) In the fourth and fifth embodiments, printing examples were described when one image forming apparatus was connected to the information processing device 1. In this embodiment, an example is described in which, when multiple image forming apparatuses are connected to the information processing device 1, an image forming apparatus that is estimated to produce fewer image defects is selected for each print job and printing is performed. In this description, it is assumed that two image forming apparatuses, image forming apparatus 2A and image forming apparatus 2B, are connected to the information processing device 1. The following mainly describes the differences between this embodiment and the fourth and fifth embodiments.

[0084] <Functional configuration of information processing device 1> Figure 26 is a diagram showing an example of the functional configuration of the information processing device in the sixth embodiment. The functional configuration of the information processing device 1 will be described below using Figure 26. The information processing device 1 includes a print job data acquisition unit 2201, an image defect information holding unit 302, a defect manifestation area estimation unit 2601, a print job selection unit 2602, a print job print instruction unit 2603, and a print instruction result display unit 2604. The print job data acquisition unit 2201 is the same as in the fourth embodiment, so its description will be omitted. The image defect information holding unit 302 is the same as in the first embodiment, so its description will be omitted. The defect manifestation area estimation unit 2601 estimates the defect manifestation areas in each image forming apparatus for each print job and creates a defect manifestation area list. The print job selection unit 2602 selects a print job to assign to each image forming apparatus based on the defect manifestation area list for each print job created by the defect manifestation area estimation unit 2601. The print job printing instruction unit 2603 issues instructions to each image forming apparatus to print the image data of the print job selected by the print job selection unit 2602. The print instruction result display unit 2604 displays the print instruction result from the print job printing instruction unit 2603 on the display 104.

[0085] <Processing by Information Processing Device 1> Figure 27 is a flowchart illustrating the processes executed in the functional configuration of the information processing device shown in Figure 26. The processes of the information processing device 1 will be described below using Figure 27. The processes shown in Figure 27 are realized by the CPU 101 executing a program stored in RAM 103 or ROM 102. The processes shown in Figure 27 are executed when instructions are received from the user via the operation unit 105 in Figure 1. Note that some or all of the steps in Figure 27 may be implemented by hardware such as an ASIC or electronic circuit. The symbol "S" in the description of each process indicates a step in the flowchart. Furthermore, the processes shown in Figure 27 can also be implemented as a cloud computing configuration where a single function is shared and processed collaboratively by multiple resources via the internet, as long as they realize each function of the information processing device 1 in Figure 26.

[0086] Since S2301 is the same as in the fourth embodiment, its explanation is omitted. In S2701, the defect manifestation area estimation unit 2601 repeats the processing in S2702 to S2706 for each print job image data acquired in S2301. Assume that each print job is assigned an ID with the alphabet a, b, ... In S2702, the defect manifestation area estimation unit 2501 initializes the defect manifestation area list for the print job ID. The defect manifestation area list is a list LCD that holds the defect manifestation areas generated by each image forming apparatus. Here, the suffix c of L indicates the print job ID, and the suffix d of L indicates the image forming apparatus ID. After initialization, LCD has a value that indicates there are no defect manifestation areas in the entire image data area. In S2703, the defect manifestation area estimation unit 2601 repeats the processing in S2704 to S2706 for each image forming apparatus connected to the information processing device 1. Assume that each image forming apparatus is assigned an ID number, such as 1, 2, ... In S2704, the defect manifestation area estimation unit 2601 refers to the information in the image defect information holding unit 302 and determines whether image defect information exists for the image forming apparatus selected in S2703. If image defect information exists for the image forming apparatus, the process in S2705 is executed; if no image defect information exists, the loop processing for the image forming apparatus is terminated. In S2705, the defect manifestation area estimation unit 2601 estimates the areas where image defects are likely to be noticeable when the image data of the print job to be processed is printed by the image forming apparatus to be processed. Specifically, area estimation is performed by applying the process in S403 of the information processing device 1 in the first embodiment to the image data. In S2706, the defect manifestation area estimation unit 2601 stores the defect manifestation areas estimated in S2705 in the defect manifestation area list LCD. In S2707, the print job selection unit 2602 selects a job to assign to the image forming apparatus based on the defect manifestation area list LCD created in S2701 to S2706. Specifically, the job is selected according to the flowchart shown in Figure 28. Details will be described later. In S2708, the print job print instruction unit 2603 instructs each image forming apparatus to execute the print job selected in S2707.In S2709, the print instruction result display unit 2604 displays the print instruction result for the image forming apparatus 2 on the display 104 of the information processing apparatus 1. Similar to the first embodiment, a notification message is displayed in the notification window 1201 shown in FIG. 12. The notification message is, for example, "Printing (image forming apparatus 2): <file name of the print job selected as the print target in the image forming apparatus 2>". Alternatively, the communication message may be "Printing (image forming apparatus 3): <file name of the print job selected as the print target in the image forming apparatus 3>", "Printing on hold: <file name of the print job not selected as the print target>".

[0087] <Processing of S2707> FIG. 28 shows the processing of S2707. In S2801, the print job selection unit 2602 initializes the printable job list. The printable job list Pd is a list that holds the printable print job IDs in each image forming apparatus. Here, the suffix d of P indicates the ID of the image forming apparatus. By the initialization, an empty list without a print job ID is created. In S2802, the print job selection unit 2602 sorts the print jobs based on the defective manifestation area list Lcd. First, Kall is calculated for the defective manifestation areas stored in the defective manifestation area list, and L’cd is created by setting 1 when Kall is greater than the threshold ThR and 0 when it is smaller. Next, for each print job, the number L’c of printable image forming apparatuses is calculated. The calculation of the number of image forming apparatuses is performed by the following formula.

[0088]

Equation

[0089] The print jobs are sorted in ascending order of L'c value. In S2803, the print job selection unit 2602 processes the print jobs in the order sorted in S2802. In S2804, the print job selection unit 2602 adds the printable job list Pd to which the print job to be processed will be printed. If L'c=0, there are no printable image forming machines, so the process ends without adding it to the printable job list Pd. If L'c>0, the image forming machine with the fewest number of jobs added to the printable job list Pd among the image forming machines with Lcd=1 is selected as the image forming machine to which the print job will be assigned. Then, the print job ID to be processed is added to the printable job list Pd.

[0090] <Effects of the 6th Embodiment> With this embodiment, print jobs can be assigned to image forming apparatuses that are less prone to image defects, thereby reducing the downtime of the image forming apparatus.

[0091] <Other Embodiments> Although various examples and embodiments of this disclosure have been described above, the spirit and scope of this disclosure are not limited to the specific descriptions herein. This disclosure is not limited to the embodiments described above, and various modifications may be made. Furthermore, this disclosure may combine some of the embodiments described above as appropriate.

[0092] (Variation 1) For example, while we have described an example where the image forming apparatus 2 is an electrophotographic printer, it is not limited to this. For example, the image forming apparatus 2 may be a full multi-inkjet system. In a full multi-inkjet system, defective images caused by nozzle abnormalities occur at random positions in the paper feeding direction, but at fixed positions in the main scanning direction. Therefore, it is possible to estimate the area where defects are apparent.

[0093] (Modification 2) Furthermore, while an example in which the information processing device 1 and the image forming apparatus 2 are configured separately has been described, the invention is not limited to this example. For example, a controller (not shown) of the image forming apparatus 2 may implement the functions of the information processing device 1. Also, when no particular distinction is made between the information processing device 1 and the controller (not shown) of the image forming apparatus 2, they will be referred to as control devices.

[0094] The present invention can also be realized by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions. Furthermore, the program may be recorded on a recording medium readable by a computer and provided.

[0095] The disclosure of this embodiment includes configurations represented by the following control device, image forming system, control method, and program.

[0096] <Configuration 1> A control device for an image forming apparatus, An acquisition means for acquiring image defect information indicating image defects that may occur in the image formed by the image forming apparatus, An estimation means for estimating defect manifestation areas where the image defect is expected to become apparent when the image forming apparatus performs printing based on the print data, based on the aforementioned image defect information and the print data related to the input print job. A control device comprising: a determination means for determining the processing of the print data based on the result of the estimation by the estimation means.

[0097] <Configuration 2> The control device according to Configuration 1, characterized in that the determination means determines to display the result of instructing the image forming apparatus to execute the print job when the defect manifestation area where the image defect is expected to become apparent is estimated, and determines to have the image forming apparatus execute the print job when the defect manifestation area where the image defect is expected to become apparent is not estimated.

[0098] <Structure 3> The control device according to Configuration 1, further comprising an instruction means that causes the image forming apparatus, which has been determined by the determination means to execute the print job, to execute the print job, and that, if the image forming apparatus, which has been determined by the determination means to execute the print job, is not connected, the instruction means that prevents the image forming apparatus from executing the print job.

[0099] <Structure 4> The control device according to configuration 1, characterized in that the estimation means estimates the region of the image area formed by the print data that is at the same main scanning position as the location of the image defect as the defect manifestation region.

[0100] <Composition 5> The control device according to configuration 4, characterized in that the estimation means estimates an area of ​​the image region formed by the print data that includes at least one of characters and lines as the defect manifestation area.

[0101] <Composition 6> The control device according to configuration 4, characterized in that the estimation means estimates the area in the image region formed by the print data in which the color difference between the image defect and the surrounding area is greater than a preset color threshold as the defect manifestation area.

[0102] <Composition 7> The control device according to configuration 4, characterized in that the estimation means estimates the area in which the color difference between the image defect and the surrounding area is greater than a preset color threshold in an area where the color of the image area formed by the print data has been blurred, as the defect manifestation area.

[0103] <Structure 8> The control device according to configuration 4, characterized in that the estimation means estimates the region in which high-frequency components included in the region surrounding the image defect are less than a preset frequency component threshold among the image regions formed by the print data as the defect manifestation region.

[0104] <Composition 9> The control device according to configuration 1, characterized in that the estimation means estimates the defect manifestation area in each of the plurality of print jobs based on the print data corresponding to each of the plurality of print jobs.

[0105] <Composition 10> The control device according to configuration 9, further comprising a selection means for selecting a print job from among the plurality of print jobs that can be executed by the image forming apparatus, based on the ratio between each search region obtained by dividing the image formed by the image forming apparatus into rectangular sections and the defect manifestation region estimated by the estimation means and obtained by dividing the search region.

[0106] <Composition 11> The control device according to configuration 10, further comprising a print instruction means for giving print instructions to the image forming apparatus for the print job selected by the selection means.

[0107] <Composition 12> The control device according to configuration 10 or 11, characterized in that the selection means selects, for each image forming apparatus, a print job from among the plurality of print jobs that can be executed by the image forming apparatus.

[0108] <Composition 13> The control device according to configuration 2, characterized in that the determination means determines not to allow each image forming apparatus to form an image if the ratio between each search region obtained by dividing the image formed by the image forming apparatus into rectangular sections and the defect manifestation region estimated by the estimation means and obtained by dividing the search region is greater than a first threshold.

[0109] <Composition 14> The control device according to configuration 13, further comprising a first changing means for changing the first threshold.

[0110] <Composition 15> The control device according to configuration 1, characterized in that the estimation means estimates the defect manifestation region based on a second threshold calculated using a feature quantity representing high-frequency components as a threshold for determining whether the image defect is noticeable or not.

[0111] <Composition 16> The control device according to configuration 15, further comprising a second changing means for changing the second threshold.

[0112] <Composition 17> The system further includes a presentation means that, before allowing the user to decide whether or not to allow each image forming apparatus to form an image, presents the user with a simulated defective image that simulates the state in which the image defect occurred. The control device according to configuration 2, characterized in that the determination means receives an instruction from the user on whether or not to cause the image forming apparatus to form an image when the simulated defective image is presented, and determines whether or not to cause the image forming apparatus to form an image.

[0113] <Composition 18> The control device according to configuration 3, characterized in that the instruction means instructs the image forming apparatus whether or not to form an image based on a predetermined priority order.

[0114] <Composition 19> The control device according to configuration 18, characterized in that the instruction means determines the priority based on the likelihood of the image defect occurring.

[0115] <Composition 20> The control device according to configuration 18, characterized in that the instruction means determines the priority based on the printing cost of each image forming apparatus.

[0116] <Composition 21> An image forming system comprising a control device according to any one of configurations 1 to 11 and the image forming apparatus.

[0117] <Composition 22> A control method for a control device for an image forming apparatus, The acquisition step involves acquiring image defect information indicating image defects that may occur in the image formed by the image forming apparatus, An estimation step in which, based on the aforementioned image defect information and the print data related to the input print job, an estimation of defect manifestation areas in which the image defect is expected to become apparent when the image forming apparatus performs printing based on the print data; An information processing method characterized by comprising: a decision step of determining the processing of the print data based on the results of the estimation step.

[0118] <Composition 23> A program for causing a computer to function as a control device as described in any one of configurations 1 to 11. [Explanation of symbols]

[0119] 1. Information Processing Device 301 Print Data Acquisition Unit 302 Image Defect Information Storage Unit 303 Defect manifestation area estimation unit

Claims

1. A control device for an image forming apparatus, An acquisition means for acquiring image defect information indicating image defects that may occur in the image formed by the image forming apparatus, An estimation means for estimating defect manifestation areas where the image defect is expected to become apparent when the image forming apparatus performs printing based on the print data, based on the aforementioned image defect information and the print data related to the input print job. A control device comprising: a determination means for determining the processing of the print data based on the estimation result of the defect manifestation area by the estimation means.

2. The control device according to claim 1, characterized in that the determination means determines to display the result of instructing the image forming apparatus to execute the print job when an area where an image defect is expected to become apparent is estimated, and determines to have the image forming apparatus execute the print job when no area where an image defect is expected to become apparent is estimated.

3. The control device according to claim 1, further comprising an instruction means that causes the image forming apparatus, which has been determined by the determination means to execute the print job, to execute the print job, and, if the image forming apparatus, which has been determined by the determination means to execute the print job, is not connected, the instruction means that prevents the image forming apparatus from executing the print job.

4. The control device according to claim 1, characterized in that the estimation means estimates the region of the image area formed by the print data that is at the same main scanning position as the location of the image defect as the defect manifestation region.

5. The control device according to claim 4, characterized in that the estimation means estimates an area of ​​the image region formed by the print data that includes at least one of characters and lines as the defect manifestation area.

6. The control device according to claim 4, characterized in that the estimation means estimates the area in the image region formed by the print data in which the color difference between the image defect and the surrounding area is greater than a preset color threshold as the defect manifestation area.

7. The control device according to claim 4, characterized in that the estimation means estimates the area in which the color difference between the image defect and the surrounding area is greater than a preset color threshold in an area where the color of the image area formed by the print data has been blurred, as the defect manifestation area.

8. The control device according to claim 4, characterized in that the estimation means estimates the region in which high-frequency components included in the region surrounding the image defect are less than a preset frequency component threshold among the image regions formed by the print data as the defect manifestation region.

9. The control device according to claim 1, characterized in that the estimation means estimates the defect manifestation area in each of the plurality of print jobs based on the print data corresponding to each of the plurality of print jobs.

10. The control device according to claim 9, further comprising a selection means for selecting a print job from among the plurality of print jobs that can be executed by the image forming apparatus, based on the ratio between each search region obtained by dividing the image formed by the image forming apparatus into rectangular sections and the defect manifestation region estimated by the estimation means and obtained by dividing the search region.

11. The control device according to claim 10, further comprising a print instruction means for giving a print instruction to the image forming apparatus for the print job selected by the selection means.

12. The control device according to claim 10 or 11, wherein the selection means selects, for each image forming apparatus, a print job from among the plurality of print jobs that can be executed by the image forming apparatus.

13. The control device according to claim 2, wherein the determination means determines not to allow each image forming apparatus to form an image if the ratio between each search region obtained by dividing the image formed by the image forming apparatus into rectangular sections and the defect manifestation region estimated by the estimation means and obtained by dividing the search region is greater than a first threshold.

14. The control device according to claim 13, further comprising a first changing means for changing the first threshold.

15. The control device according to claim 1, characterized in that the estimation means estimates the defect manifestation region based on a second threshold calculated using a feature quantity representing high-frequency components as a threshold for determining whether the image defect is noticeable or not.

16. The control device according to claim 15, further comprising a second changing means for changing the second threshold.

17. The system further includes a presentation means that, before allowing the user to decide whether or not to allow each image forming apparatus to form an image, presents the user with a simulated defective image that simulates the state in which the image defect occurred. The control device according to claim 2, characterized in that the determination means receives an instruction from the user whether or not to cause the image forming apparatus to form an image when the simulated defective image is presented, and determines whether or not to cause the image forming apparatus to form an image.

18. The control device according to claim 3, characterized in that the instruction means instructs the image forming apparatus whether or not to form an image based on a predetermined priority order.

19. The control device according to claim 18, characterized in that the instruction means determines the priority based on the likelihood of the image defect occurring.

20. The control device according to claim 18, characterized in that the instruction means determines the priority based on the printing cost of each image forming apparatus.

21. An image forming system comprising the control device according to any one of claims 1 to 11 and the image forming apparatus.

22. A control method for a control device for an image forming apparatus, An acquisition step of acquiring image defect information indicating image defects that may occur in the image formed by the image forming apparatus, An estimation step in which, based on the aforementioned image defect information and the print data related to the input print job, an estimation of defect manifestation areas in which the image defect is expected to become apparent when the image forming apparatus performs printing based on the print data; An information processing method characterized by comprising: a decision step of determining the processing of the print data based on the results of the estimation step.

23. A program for causing a computer to function as a control device according to any one of claims 1 to 11.

Images