Information processing device, information processing system, image analysis method, and control program
The information processing device with a second image analysis unit addresses the challenge of identifying complex image unevenness by performing additional inspections across multiple devices, reducing load and enhancing detection accuracy.
Patent Information
- Application Number
- JP2021125027
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2021-07-30
- Publication Date
- 2025-08-05
- Estimated Expiration
- 2041-07-30
AI Technical Summary
Existing image forming technologies struggle to accurately identify the cause of image unevenness that does not coincide with the rotation period of a single component, and the increasing number of cycles exacerbates calculation load, making it difficult to detect and address such issues effectively.
An information processing device communicatively connected to image forming devices performs additional inspections with a second image analysis unit that detects image unevenness with cycles different from the first unit, aggregates data from multiple devices, and generates diagnostic reports to reduce processing load and enhance detection accuracy.
The solution reduces the processing load on image forming devices and enables highly accurate detection of image defects, including periodic image unevenness that is difficult to identify by the devices themselves.
Smart Images

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Abstract
Description
[Technical Field]
[0001] The present invention relates to an information processing device, an information processing system, an image analysis method, and a control program. [Background technology]
[0002] 2. Description of the Related Art There is an inspection technique in which an image formed on a recording material such as paper by an image forming apparatus is read by a reading device provided in the image forming apparatus or a post-processing apparatus, and the quality of the image is judged.
[0003] Patent Document 1 discloses a technology for an image forming apparatus that uses an inspection sensor inside the apparatus to identify the cause of periodic image occurrence. In this image forming apparatus, the inspection sensor detects images printed on multiple consecutive sheets of recording material, extracts information about the periodic image from the difference with the corresponding image data, and identifies the cause of occurrence by matching the detected occurrence interval with the stored rotation period of the apparatus configuration. [Prior art documents] [Patent documents]
[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2009-020215 Summary of the Invention [Problem to be solved by the invention]
[0005] However, while the technology of Patent Document 1 can identify the part that caused the image unevenness (periodic image) whose period coincides with the rotation period stored in the storage unit, the image unevenness does not necessarily occur with the rotation period of a single component. For example, image unevenness can occur due to various constituent elements, such as interference between multiple components or inconsistencies in control parameters related to rotation speed. With the technology of Patent Document 1, it is difficult to identify the cause of such problems in advance and address them.
[0006] Furthermore, as the number of cycles to be inspected increases, the load on the calculation process also increases, making it difficult to simply increase the number of cycles.In addition, the strength and visibility of image unevenness that occurs varies, so it can be difficult to identify the cycle of image unevenness from the output results of a single image forming device.
[0007] The present invention has been made in consideration of the above circumstances, and a first object of the present invention is to provide an information processing device and an image processing method that can reduce the load on the calculation processing of an image forming device and detect image defects with high accuracy.
[0008] A second object of the present invention is to provide an information processing apparatus and an image processing method that can identify the period of image unevenness that is difficult to detect by the image forming apparatus itself. [Means for solving the problem]
[0009] The above object of the present invention can be achieved by the following means.
[0010] (1) An information processing device that is communicatively connected to one or more image forming devices that include an image forming unit, an image reading unit, and a first image analysis unit that detects image defects related to predetermined inspection items for read image data, an acquiring unit that acquires, from the image forming apparatus, original inspection data based on the read image data obtained by reading an image of a recording medium on which an image is formed by the image forming unit with the image reading unit; a second image analysis unit that performs an inspection on the original inspection data with inspection content different from that of the inspection performed by the first image analysis unit; An information processing device comprising:
[0011] (2) The predetermined inspection items to be performed by the first image analysis unit include an inspection of image unevenness having one or more specific cycles; The information processing device according to (1) above, wherein the second image analysis unit inspects image unevenness having a cycle other than the cycle inspected by the first image analysis unit.
[0012] (3) The predetermined inspection items to be performed by the first image analysis unit include an inspection of image unevenness having one or more specific cycles; The information processing device according to (1) or (2) above, wherein the second image analysis unit performs a detection process to detect the occurrence of image unevenness of a new period other than the period inspected by the first image analysis unit.
[0013] (4) The information processing device described in (3) above, wherein the second image analysis unit, in the detection process, detects periodic image unevenness that commonly occurs in the multiple pieces of inspection source data acquired from the multiple image forming devices.
[0014] (5) An information processing device that is communicatively connected to a plurality of image forming devices each having an image forming unit and an image reading unit, an acquiring unit that acquires, from the image forming apparatus, original inspection data based on read image data obtained by reading an image of a recording medium on which an image is formed by the image forming unit with the image reading unit; a second image analysis unit that executes a detection process for detecting image unevenness with a new period other than the period inspected by predetermined inspection items, including inspection items related to image unevenness with one or more specific periods, in the plurality of pieces of inspection original data acquired from the plurality of image forming devices; and An information processing device comprising:
[0015] (6) The image forming apparatus includes a first image analysis unit that detects image defects related to the predetermined inspection items from the scanned image data; The information processing device according to (5) above, wherein the second image analysis unit detects image unevenness of a new cycle other than the cycle inspected by the first image analysis unit based on the inspection item.
[0016] (7) The information processing device according to (5) above, further comprising a first image analysis unit that detects defects in an image relating to the predetermined inspection item for the original inspection data.
[0017] (8) The acquisition unit acquires device information indicating at least one of the model, hardware version, software version, setting conditions, installed parts, and usage history of the image forming devices from the plurality of image forming devices; An information processing device described in any of (4) to (7) above, wherein the detection processing of the second image analysis unit detects commonly occurring periodic image unevenness in the inspection source data obtained from image forming devices that have some or all of the device information in common among the multiple inspection source data.
[0018] (9) The second image analysis unit performs a frequency analysis process on the original inspection data, An information processing device described in any of (4) to (8) above, which determines an amplitude or intensity judgment threshold for determining defects based on the distribution of amplitude or intensity of multiple image forming devices in a target period of the commonly occurring image unevenness detected by the detection process.
[0019] (10) An information processing device according to any one of (1) to (4), (6), and (7), comprising an output unit that integrates defects detected by the first image analysis unit and defects detected by the second image analysis unit, and, when multiple defects are detected, generates a report that assigns priority to the defects or displays them in order of priority.
[0020] (11) An information processing device according to any one of (1) to (4), (6), (7), and (10), comprising an output unit that integrates defects detected by the first image analysis unit and defects detected by the second image analysis unit, and generates a report including a composite image in which a marking image indicating the location where the defect occurred is superimposed on an image generated from the original inspection data.
[0021] (12) An image forming apparatus including an image forming unit, an image reading unit, and a first image analysis unit that detects defects related to predetermined inspection items in the read image data; An information processing device according to any one of (1) to (6) above; An information processing system comprising:
[0022] (13) An image analysis method executed by an information processing device communicatively connected to one or more image forming devices including an image forming unit, an image reading unit, and a first image analysis unit that detects image defects related to predetermined inspection items for read image data, a step (a) of acquiring, from the image forming apparatus, original inspection data based on the read image data obtained by reading, with the image reading unit, an image of a recording medium on which an image has been formed by the image forming unit; and (b) inspecting the original inspection data with inspection content different from that of the inspection performed by the first image analysis unit.
[0023] (14) The predetermined inspection items to be performed by the first image analysis unit include an inspection of image irregularities of one or more specific periods, The image analysis method according to (13) above, wherein in the step (b), an inspection is performed for image unevenness having a cycle other than the cycle inspected by the first image analysis unit.
[0024] (15) The image analysis method described in (13) or (14) above, wherein step (b) further includes a detection process for detecting the occurrence of image unevenness of a new period other than the period inspected by the first image analysis unit.
[0025] (16) The image analysis method described in (15) above, wherein the detection process in step (b) detects common periodic image unevenness in multiple pieces of inspection source data obtained from multiple image forming devices.
[0026] (17) An image analysis method executed by an information processing device communicatively connected to a plurality of image forming apparatuses each having an image forming unit and an image reading unit, a step (a) of acquiring, from the image forming apparatus, original inspection data based on read image data obtained by reading, with the image reading unit, an image of a recording medium on which an image has been formed by the image forming unit; and (b) executing a detection process for detecting image unevenness with a new period other than the period inspected by predetermined inspection items, including inspection items related to image unevenness with one or more specific periods, in the inspection source data acquired from the image forming devices, the image unevenness having a new period that commonly occurs.
[0027] (18) In the step (a), device information indicating at least one of the model, hardware version, software version, setting conditions, installed parts, and usage history of the image forming devices is acquired from the plurality of image forming devices; The image analysis method described in (16) or (17) above, wherein the detection process in step (b) detects commonly occurring periodic image unevenness in the inspection source data obtained from image forming devices that have some or all of the device information in common among the multiple inspection source data.
[0028] (19) A control program for causing a computer to execute the image analysis method according to any one of (13) to (18) above. [Effects of the Invention]
[0029] The information processing device of the present invention includes an acquisition unit that acquires, from an image forming device, original inspection data based on image data obtained by reading an image of a recording medium on which an image has been formed by a first image forming unit with an image reading unit, and a second image analysis unit that performs an inspection on the original inspection data that is different from the inspection performed by the first image analysis unit of the image forming device. This reduces the processing load of the image forming device and enables highly accurate detection of image defects.
[0030] The information processing device of the present invention also includes a second image analysis unit that executes a detection process for detecting periodic image unevenness that occurs commonly in a plurality of pieces of original inspection data acquired from a plurality of image forming devices, the period of which is new, other than the period inspected by predetermined inspection items, including inspection items related to image unevenness with one or more specific periods, for the original inspection data. In this way, it is possible to identify the period of image unevenness that is difficult to detect by the image forming device itself. [Brief explanation of the drawings]
[0031] [Figure 1] 1 is a schematic diagram showing an information processing system including an information processing apparatus according to a first embodiment and an image forming apparatus connected thereto. [Figure 2] 1 is a cross-sectional view showing a schematic configuration of an image forming apparatus. [Figure 3] FIG. 2 is a block diagram illustrating a hardware configuration of the image forming apparatus. [Figure 4] FIG. 2 is a block diagram showing a hardware configuration of the information processing device. [Figure 5] 10 is a table showing an example of device information. [Figure 6] 10 is a flowchart illustrating an inspection process of the image forming apparatus. [Figure 7] 10 is a table showing an example of a first test item. [Figure 8] 10 is a flowchart showing an inspection process of the information processing device. [Figure 9] 10 is a subroutine flowchart showing the detection process of step S22. [Figure 10] 10 is a table showing examples of second test items. [Figure 11] FIG. 10 is a diagram illustrating an example of frequency analysis processing. [Figure 12] FIG. 10 is a diagram illustrating an example of frequency analysis processing. [Figure 13] FIG. 10 is a diagram illustrating an example of frequency analysis processing. [Figure 14A] 1 is an example of a diagnostic report. [Figure 14B] 1 is an example of a diagnostic report. [Figure 15] FIG. 10 is a block diagram showing a hardware configuration of an information processing device according to a second embodiment. [Figure 16] 10 is a flowchart showing an inspection process. [Figure 17] 10 is a subroutine flowchart showing the detection process of step S22 (or S42) in the second modified example. DETAILED DESCRIPTION OF THE INVENTION
[0032] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicate explanations will be omitted. Furthermore, the dimensional proportions in the drawings are exaggerated for the convenience of explanation and may differ from the actual proportions.
[0033] (First embodiment) FIG. 1 is a schematic diagram illustrating an information processing system 500 according to a first embodiment. The information processing system 500 includes an information processing device 50 and one or more image forming devices 10. In the example illustrated in FIG. 1, the information processing system 500 includes the information processing device 50, which includes multiple image forming devices 10. The terminal device 70 is a PC, tablet device, smartphone, or the like, and is used by users, such as service staff who maintain and manage the image forming devices 10. These devices are connected to each other via a network. The information processing device 50 functions as a server, such as a web server or database server. The information processing device 50 aggregates original inspection data, device information, and primary inspection results, which are periodically (e.g., daily) sent from each image forming device 10, and performs additional inspection and analysis, as described below, to generate a diagnostic report indicating the status of each image forming device 10. The service staff can refer to the generated diagnostic report via the terminal device 70 to help maintain and manage the image forming device 10.
[0034] (Image forming apparatus 10) Fig. 2 is a cross-sectional view showing a schematic configuration of the image forming apparatus 10. Fig. 3 is a block diagram showing a hardware configuration of the image forming apparatus 10.
[0035] As shown in these figures, the image forming device 10 comprises a control unit 11, a memory unit 12, an image forming unit 13, a paper feed and conveying unit 14, an operation display unit 15, a reading device 16, and a communication unit 19, which are interconnected via a bus or the like for exchanging signals.
[0036] (Control unit 11, memory unit 12) The control unit 11 is a CPU, and controls each unit of the device and performs various calculation processes according to a program. The control unit 11 functions as a first image analysis unit 111. The first image analysis unit 111 inspects the read image data generated by the reading device 16. This inspection includes periodic inspections (regular inspections) to determine the state of the image forming device 10, and product inspections to check whether the product (printed material on which an image has been formed) is output normally. The periodic inspections will be described later. In product inspections, the read image data obtained by reading the printed material is compared with the print data (original data) to check whether they are normal.
[0037] The storage unit 12 includes a ROM for storing various programs and data in advance, a RAM for temporarily storing programs and data as a working area, a hard disk for storing various programs and data, etc. The storage unit 12 stores print data (hereinafter also referred to as "inspection patterns") such as scanned image data, halftones used in periodic inspections, color charts with color patches of multiple colors, and inspection charts with multiple grid images and register marks for detecting misalignment, inspection items (first inspection item(s)), and device information about the device itself (see FIG. 5 described below).
[0038] (Image forming unit 13) The image forming unit 13 forms images, for example, by electrophotography, and includes writing units 131 and image creating units corresponding to each of the primary colors (Y (yellow), M (magenta), C (cyan), and K (black)). Each image creating unit includes a photosensitive drum 132, a charging electrode (not shown), a developing unit 133 containing a two-component developer consisting of toner and carrier, and a cleaning unit (not shown). The toner images formed in the image creating units for each color are superimposed on an intermediate transfer belt 134 and transferred to paper 90 (also referred to as a recording medium) conveyed by a secondary transfer unit 135. The (full-color) toner image on paper 90 is fixed to paper 90 by applying heat and pressure in a fixing unit 136 located downstream.
[0039] (Paper feed conveyance section 14) The paper feed conveyance unit 14 includes a plurality of paper feed trays 141, conveyance paths 142, 143, 145, and 147, a plurality of conveyance rollers arranged on these conveyance paths 142, 143, 145, and 147, and a drive motor (not shown) that drives these. Paper 90 fed from the paper feed tray 141 is conveyed along the conveyance path 142, an image is formed on the paper by the image forming unit 13, the paper is sent downstream, and after being read by the reading device 16 depending on the settings, the paper is discharged to the paper output tray 148 or the paper output tray 149.
[0040] Furthermore, if the print setting of the print job is double-sided printing, the paper 90 with an image formed on one side (first side) is transported to the ADU transport path 143 located at the bottom of the image forming device 10. The paper 90 transported to this ADU transport path 143 is turned over on a switchback path, and then merges with the transport path 142, where an image is again formed on the other side (second side) of the paper 90 by the image forming unit 13.
[0041] (Operation display section 15) The operation display unit 15 includes a touch panel, a numeric keypad, a start button, a stop button, etc., and is used to display the status of the image forming apparatus 10 and to input various settings and instructions by the user. In addition, if an abnormality is detected in the proof inspection by the control unit 11 or in the inspection by the first image analysis unit 111 of the control unit 11, the inspection result may be displayed.
[0042] (Reader 16) The reading device 16 has image reading units 161 and 162, and a spectrophotometer 163. These are arranged so that the reading area is on the conveying path 145. The image reading units 161 and 162 are scanners and have the same configuration. The image reading units 161 and 162 are arranged so that they each read images on different sides of the paper 90. If double-sided printing is set, the image reading unit 161 reads the bottom side (first side) of the paper 90, and the image reading unit 162 reads the top side (second side). If single-sided printing is set, only the image reading unit 162 reads the image on the front side of the paper 90.
[0043] The control unit 11 performs color adjustment and image position adjustment by analyzing the scanned image data obtained by scanning an inspection pattern with patches of multiple colors and thin lines during regular inspections (for example, when starting up the device every morning). At the same time, it also performs image analysis of a halftone inspection pattern with a uniform density across the entire surface to detect image defects.
[0044] The image reading unit 161 (or 162) includes a sensor array, a lens optical system, an LED (Light Emitting Diode) light source, and a housing for accommodating these components.
[0045] The sensor array is a color line sensor in which multiple optical elements (e.g., CCDs (Charge Coupled Devices)) are arranged in a line along the main scanning direction, and the reading area in the width direction corresponds to the entire width of the paper 90. The optical system is composed of multiple mirrors and lenses. Light from the LED light source passes through the document glass and illuminates the surface of the paper 90 as it passes the reading position on the transport path 145. The image of this reading position is guided by the optical system and formed on the sensor array.
[0046] (Spectrophotometer 163) The spectrophotometer 163 spectrally measures the color of each color patch of the color evaluation image formed on the paper 90 by the image forming unit 13 on the conveying path 145, and can obtain the spectral reflectance of each wavelength in the visible light range and its neighboring range. The color measurement data can be output in a color system such as XYZ. Each color patch of this evaluation image is similarly read by the image reading unit 161 or the image reading unit 162, as described below, and converted into data in the same color system such as XYZ. Then, by comparing both sets of data, the image reading units 161 and 162 are calibrated (correction values are determined).
[0047] (Communications Department 19) The communication unit 19 is an interface for the image forming apparatus 10 to communicate with external devices such as the information processing apparatus 50. The communication unit 19 may use various local connection interfaces such as network interfaces conforming to standards such as USB, Ethernet (registered trademark), and IEEE1394, and wireless communication interfaces such as Bluetooth (registered trademark) and IEEE802.11.
[0048] (information processing device 50) 4 is a block diagram showing the hardware configuration of the information processing device 50. The information processing device 50 includes a control unit 51, a storage unit 52, and a communication unit 53. These components are similar to the control unit 11, storage unit 12, and communication unit 19 described above.
[0049] (control unit 51) The control unit 51 functions as an acquisition unit 511 and an output unit 515 by working in cooperation with the communication unit 53. The control unit 51 also functions as a second image analysis unit 512. The acquisition unit 511 acquires original inspection data, device information, etc. from the image forming apparatus 10. The second image analysis unit 512 performs an inspection with different inspection content from that of the first image analysis unit. The output unit 515 generates a diagnostic report that integrates the inspection results of the first image analysis unit 111 and the second image analysis unit 112, or that includes a composite image in which an image generated from the original inspection data is marked to indicate defective locations. The output unit 515 also has a web application function, and provides the diagnostic report to a service staff member via a browser, allowing the service staff member to view the report. These functions will be described in detail below.
[0050] (Storage unit 52) Analysis data, test items (second test item(s)), and test results are stored in the storage unit 52. The test items and test results will be described later.
[0051] The analysis data is data acquired by the acquisition unit 511 from a plurality of image forming apparatuses 10. The analysis data includes inspection source data and apparatus information.
[0052] The "original inspection data" is the image scan data itself obtained by scanning the paper 90 to be inspected, or processed data that has been processed based on this data to the extent that the spatial information of the image required for inspection is not lost. For example, if the inspection target is image unevenness that occurs periodically in the paper width direction (also called the main scanning direction, hereinafter simply referred to as CD), the original inspection data is one-dimensional (vertical) processed data (hereinafter also referred to as profile data) in which pixel values in the width direction are averaged. Using profile data can reduce the data size, shorten the transmission time when transmitting to the information processing device 50, and also reduce the data volume when storing this data in the information processing device 50.
[0053] FIG. 5 is a table showing an example of device information. "Device information" includes the image forming device's model, hardware version, software version, setting conditions, installed components, and usage history. The model is also referred to as the model number or product name. The hardware version is referred to as the lot. For example, there is the initial lot version when the device was released, and the second or subsequent version with minor changes. The software version is the version of the control software written in the firmware (FW). This control software is updated as needed by service staff. "Setting conditions" include adjustment values related to image formation and paper transport of the image forming device 10. For example, these include speed adjustment values for the intermediate transfer belt 134 and secondary transfer unit 135, paper feed timing in the paper feed transport unit 14, paper transport speed, and leading edge timing. The installed components include the presence or absence of optional devices / components such as post-processing devices, and their model numbers. The usage history includes the number of sheets used and the usage time of the image forming device 10 itself and each replacement part (the photosensitive drum 132, developing unit 133, cleaning unit, and fixing unit 136). The usage history of the replacement part is reset when the service staff replaces the replacement part with a new part at the specified maintenance cycle.
[0054] (Inspection processing) Next, an explanation will be given of the inspection process performed in the information processing system 500. The inspection process explained below is a regular inspection, which is carried out, for example, each day when the image forming apparatus 10 is turned on, and some of the inspection results are sent to the information processing apparatus 50 and collected. The regular inspection includes color adjustment (color inspection), image position adjustment (image position inspection), and image defect inspection, but only the image defect inspection will be explained below, and explanations of other inspections will be omitted.
[0055] (Inspection of image forming device 10) 6 is a flowchart showing the inspection process of the image forming apparatus 10. FIG.
[0056] (Step S11) The control unit 11 causes the image forming unit 13 to form an image based on the test pattern stored in the storage unit 12, for example, image data of a full-surface halftone. For example, a plurality of full-surface, uniform halftone images of each of the single colors Y, M, C, and K are formed in succession.
[0057] (Step S12) The image reading unit 162 reads the image formed on the paper 90 by the image forming unit 13, and generates read image data.
[0058] (Step S13) The first image analysis unit 111 performs an inspection for the first inspection item on the read image data obtained in step S12.
[0059] (Inspection of the first inspection item (primary inspection)) The first inspection items are predetermined inspection items that are commonly performed in each image forming apparatus 10. As shown in Fig. 7, the first inspection items include image unevenness (period 300 mm), image unevenness (period 43 mm), vertical streaks in the paper feed direction (FD), and spot-shaped white fireflies. The first image analysis unit 111 performs inspections for each inspection item by image processing.
[0060] To inspect for periodic image irregularities in a CD, for example, pixels aligned in the width direction are averaged (corresponding to the profile data described above), and then the signal strength (amplitude) of each frequency (spatial frequency) is determined using frequency analysis such as FFT (Fast Fourier Transform), and if the signal strength is above a predetermined threshold, it is determined that an image defect exists.
[0061] Vertical streaks can be inspected, for example, by using a differential filter or the like to calculate the difference between the pixel of interest and a pixel that is a predetermined distance (number of pixels) away in the width direction, and then judging whether a vertical streak exists based on the distribution of pixels whose difference value is greater than a predetermined threshold value. Alternatively, the difference value can be averaged vertically, and if there is a difference from the average value of adjacent pixels that is greater than a predetermined threshold value, it can be judged that a vertical streak defect exists.
[0062] Inspection for point defects such as fireflies, black and white spots, and stains involves, for example, calculating the difference between pixels at corresponding positions in the read image data and the inspection pattern (original image data), extracting pixels where the difference is greater than or equal to a predetermined value, clustering the extracted pixels with adjacent pixels, and determining that there is a point defect such as a firefly if the area and / or integral value of the cluster (number of pixels x difference pixel value) is greater than or equal to a predetermined threshold.
[0063] If the number of first inspection items performed on the image forming apparatus 10 side is too large, the processing time will be long. Furthermore, since the periodic inspection on the image forming apparatus 10 side includes inspections other than the image defect inspection (color adjustment, image position adjustment, etc.) as described above, resources cannot be allocated solely to the image defect inspection processing. For these reasons, there is an upper limit to the number of first inspection items, and their contents are also limited. Therefore, some inspection items are shared and performed on the information processing apparatus 50 side as second inspection items (see FIG. 10 described below).
[0064] (Step S14) The control unit 11 transmits the test results obtained in step S13, original test data based on the scanned image data used in step S13, and device information in cooperation with the communication unit 19. This original test data is the scanned image data itself, as described above, or profile data obtained by processing the scanned image data.
[0065] (Inspection process of information processing device 50) Next, a description will be given of the inspection performed by the information processing device 50. Fig. 8 is a flowchart showing the inspection process of the information processing device 50. Fig. 9 is a subroutine flowchart showing the process of step S22 in Fig. 8, and Fig. 10 is a table showing examples of the second inspection items.
[0066] The information processing device 50 aggregates the inspection results sent by each image forming device 10 through periodic inspections as described below, and based on the original inspection data, inspects a second inspection item as an inspection content different from the inspection by the first image analysis unit 111 of the image forming device 10, or performs a detection process to detect image unevenness with an unknown period and sets (adds) this as the second inspection item.
[0067] (Step S21) Acquisition unit 511 acquires the inspection results, inspection source data, and device information in accordance with the process of step S14 described above from a plurality of image forming devices 10. Note that acquisition of device information may be omitted, or the device information may be acquired from a database (for example, in storage unit 52) that associates information that can identify the image forming device (such as a serial number) with the device information.
[0068] (Step S22) The second image analysis unit 512 of the information processing device 50 performs a process of detecting new image unevenness (unknown image unevenness). This image unevenness detection process accurately detects image unevenness that is difficult to distinguish from the output image of only one image forming device 10 by referring to the output images of multiple image forming devices 10. It is desirable to perform the process of step S22 after the original inspection data for a certain number of devices has been collected. For example, the process of step S22 (and step S23 linked thereto) is performed once a week, and other processes are performed each time (daily) the original inspection data, etc. is sent from the image forming device 20 in step S21.
[0069] (Step S301) 9, the second image analysis unit 512 performs frequency analysis such as FFT analysis on the original inspection data acquired from the multiple image forming devices 10. This original inspection data is data based on the same inspection pattern, for example, scanned image data obtained by outputting halftones of the colors Y, M, C, and K by each image forming device 10. The number of image forming devices 10 from which the original inspection data is collected can be selected as appropriate, but is preferably from several tens to several hundred.
[0070] 11 to 13 show examples of frequency analysis processing performed on profile data (detection source data).
[0071] FIG. 11(a) shows profile data from a certain image forming apparatus 10. The horizontal axis of the graph represents the position of an image corresponding to an entire sheet of paper 90, with the left side representing the leading edge and the right side representing the trailing edge. The vertical axis represents the luminance value (gray value), with the upper side being brighter and the lower side being darker (higher density). FIG. 11(b) shows the profile data after background removal processing as a pre-processing step, which removes the luminance gradient from the leading edge to the trailing edge that was present in FIG. 11(a). FIG. 11(c) shows the results of FFT analysis of the processed data from FIG. 11(b). The horizontal axis represents spatial frequency (cycles / pixel), and the vertical axis represents amplitude (intensity). Similarly, FIGS. 12 and 13 show data obtained by processing profile data acquired from a certain image forming apparatus 10.
[0072] In the example of the FFT analysis results in Figure 11(c), it can be seen that there is an amplitude peak at a period of 1.33 mm. In Figure 12(c), as another example, there is an amplitude peak at a period of 6.34 mm, and in Figure 13(c), there is an amplitude peak at a period of 17.96 mm.
[0073] (Step S302) The second image analysis unit 512 extracts the top n frequencies in order of amplitude from the FFT analysis results obtained from each profile data. n is a number, for example, five. In the example shown in FIG. 12(c), frequencies with increasing amplitude are extracted in order from the maximum peak of 6.34 mm. However, at this time, known periods (frequencies), i.e., periods that have already been detected in the first or second inspection item, are excluded. The five periods (hereinafter referred to as candidate periods) extracted from the frequency analysis results of the profile data of each image forming device 10 and the amplitude values are associated and saved (hereinafter referred to as candidate data).
[0074] (Step S303) The second image analysis unit 512 aggregates candidate data from a plurality of image forming apparatuses 10 and analyzes the occurrence status for each candidate cycle.
[0075] (Step S304) Then, the candidate cycles in which the occurrence rate is equal to or greater than a predetermined threshold value s1 or the number of occurrences is in the top m places are determined as detection targets (new inspection cycles).
[0076] (Step S305) The second image analysis unit 512 acquires the amplitude value of one or more new detection periods (frequencies) by performing frequency analysis such as FFT analysis or wavelet analysis on the profile data (or pre-processed data) that is the original inspection data of each image forming apparatus 10. Wavelet analysis takes longer to process than FFT analysis, but when the frequency of the detection target can be identified, wavelet analysis is more reliable.
[0077] The judgment threshold is then determined from the distribution of amplitude values. The second image analysis unit 512 can determine the judgment threshold by statistical processing. For statistical processing, a box plot or a normal distribution can be used. In a box plot, the third quartile is used as the judgment threshold, and in a normal distribution, +2σ is used as the judgment threshold. Image unevenness equal to or greater than the judgment threshold is determined to be a defect. This completes the processing of the subroutine in FIG. 9, and the process returns to the processing in FIG. 8.
[0078] (Step S23) The second image analysis unit 512 sets (adds) one or more new inspection cycles and determination thresholds determined in steps S304 and S305 as new inspection items to the second inspection items. Note that the new inspection items may be moved to the first inspection items depending on the incidence rate, etc., while taking into consideration the upper limit of the number of the first inspection items performed on the image forming apparatus 10 side.
[0079] (Step S24) The second image analysis unit 512 performs an inspection of the target image forming apparatus 10 based on the inspection source data for the second inspection item (secondary inspection). As shown in Fig. 10, the second inspection items are different from the first inspection items, and in particular include image unevenness (1.5 mm period), image unevenness (6 mm period), image unevenness (18 mm period), etc., which have periods other than those inspected by the first inspection items (see Fig. 7). The second inspection items are those set by the processing of the immediately preceding step S22 (particularly S304-S305) or those set by the processing of step S22 earlier than this (the detection processing of Fig. 9 that was previously executed).
[0080] (Step S25) The output unit 515 generates a diagnostic report from the inspection results obtained by the above processing and stores it in the storage unit 52. Then, this diagnostic report is output to the terminal device 70 of the service staff in response to a request from the terminal device 70 by the web application function of the output unit 515. By viewing the diagnostic report, the service staff can refer to the occurrence status and level of image defects and the estimated causes, and use this information to help with the maintenance and management of the image forming apparatus 10.
[0081] 14A and 14B are examples of diagnostic reports. One diagnostic report consists of multiple pages (generally a dozen or so pages), and these figures show a portion of the diagnostic report. FIG. 14A is the first page p01, and FIG. 14B is the seventh page following it. p07 shows the scanned image data obtained by scanning the output side of a Y-color halftone inspection pattern (labeled "horizontal streak evaluation chart" in the figure). The first pages p01 and p02 (not shown) of the diagnostic report contain information identifying the target image forming device 10 (serial number), as well as device information such as the model and usage history.
[0082] The diagnostic report may also integrate the defects detected by the first image analysis unit 111 and the second image analysis unit 512 and assign a priority (level of importance) to each defect. The inspection results (primary inspection results) of the first image analysis unit 111 may be obtained, for example, in step S21 from the image forming apparatus 10 along with other information. The diagnostic report may display the results in order of priority. For example, in FIG. 14A, column a11 of page p01 displays the analysis results for the first inspection item by the first image analysis unit 111, and column a12 displays the analysis results for the second inspection item by the second image analysis unit 512, thereby displaying the defects detected by both analysis units in an integrated manner. Each defect may also be assigned a priority (rank), or the defects may be displayed in order of priority. The estimated causes of each defect may also be displayed. The causes of each defect are pre-associated with the inspection item as shown in FIGS. 7 and 10. The cause of the occurrence may be automatically set by the control unit 51 as a component that operates at a rotational period corresponding to the period of the image unevenness, or a component that has been identified through research and investigation by a person in charge at the manufacturing company of the image forming device 10 may be set as the cause of the occurrence.
[0083] Pages p03 to p06 (all not shown) display a list of scanned image data spanning multiple pages that were sent from image forming apparatus 10 (steps S14 and S21) and output continuously. Of these, page p03 displays thumbnails of scanned images of a yellow halftone test pattern printed by Y developing unit 133 on 12 consecutive sheets of paper 90. Pages p04 to p06 are also pages of different colors corresponding to page p03, and display thumbnails of magenta, cyan, and black images, respectively.
[0084] Pages p07 (FIG. 14B) and p08 to p10 (all not shown) are enlarged views of one of the images included in pages p03 to p06. If a defect is detected, a marking image indicating the location of the defect may be displayed. Page p07 (FIG. 14B) displays a composite image in which a marking image indicating the location of the defect is superimposed on image i01 based on the original inspection data. On page p07, the type of defect (inspection item: image unevenness, 18 mm, 1.5 mm, 6 mm period) is displayed next to the marking image (see the enlarged view in FIG. 14B). In particular, if the defect is image unevenness, the marking image is a cage-shaped line diagram corresponding to the period. A rank may also be displayed along with the type of defect. The higher the rank number, the worse the severity, and a rank of 1.0 or higher is determined to be NG (defective).
[0085] As described above, the information processing apparatus according to the first embodiment includes an acquisition unit that acquires original inspection data from the image forming apparatus, and a second image analysis unit that performs an inspection on the original inspection data that is different from the inspection performed by the first image analysis unit of the image forming apparatus, thereby reducing the processing load on the image forming apparatus and enabling highly accurate detection of image defects.
[0086] In particular, in this embodiment, the second image analysis unit executes a detection process (FIG. 9) to detect image unevenness of a new cycle other than the cycle inspected by the first image analysis unit, which is image unevenness that occurs commonly in a plurality of image forming apparatuses. By providing such a configuration, image unevenness of a new cycle can be detected with high accuracy.
[0087] (Second embodiment) In the first embodiment, the image forming apparatus 10 is provided with the first image analysis unit, but in the second embodiment described below, the information processing apparatus 50b is provided with the first image analysis unit. Fig. 15 is a block diagram showing the hardware configuration of the information processing apparatus 50b according to the second embodiment. Note that in the second embodiment, the configuration other than that shown in Fig. 15 is the same as that of the first embodiment, including Fig. 1, and therefore description thereof will be omitted.
[0088] 15, the information processing device 50b includes a control unit 51b, a storage unit 52, and a communication unit 53. The configurations of the storage unit 52 and the communication unit 53 are similar to those of the information processing device 50 according to the first embodiment, and therefore, description thereof will be omitted.
[0089] The control unit 51b functions as an acquisition unit 511, a first image analysis unit 513, a second image analysis unit 514, and an output unit 515. The acquisition unit 511 and the output unit 515 have the same functions as the corresponding components in the first embodiment, and therefore, description thereof will be omitted.
[0090] The first image analysis unit 513 has the same function as the first image analysis unit 111 (see FIG. 3) of the image forming apparatus 10 of the first embodiment. That is, the first image analysis unit 513 of the second embodiment detects image defects related to a third inspection item(s) that are predetermined for the inspection source data (scanned image data or profile data). The third inspection items include the first inspection items shown in FIG. 7. Furthermore, unlike the image forming apparatus 10, there are almost no resource constraints, and therefore the second inspection items shown in FIG. 10 may further include inspection items that have become known in a previous image unevenness detection process (step S22 or step S42 described below). The second image analysis unit 514 detects image unevenness with a new period other than the period inspected by the first image analysis unit 513 based on the known predetermined inspection items.
[0091] (Inspection process of information processing device 50) FIG. 16 is a flowchart showing the inspection process of the information processing device 50.
[0092] (Step S40) Here, the acquiring unit 511 acquires the inspection original data and the device information from each of the multiple image forming devices 10.
[0093] (Step S41) The first image analysis unit 513 performs an inspection on the original inspection data acquired in step S40 regarding a predetermined third inspection item.
[0094] (Step S42) The second image analysis unit 514 performs a process of detecting new image unevenness (unknown image unevenness). The process of detecting image unevenness in step S44 is also performed according to the subroutine flowchart shown in FIG.
[0095] (Step S43) As in step S23, the second image analysis unit 514 sets (adds) one or more new inspection frequencies and judgment thresholds determined in the processing of Figure 9 as new inspection items to the third inspection item.
[0096] (Step S44) The second image analysis unit 514 performs an inspection for the third inspection item from the inspection source data on the target image forming apparatus 10. Note that since the processing already overlaps with step S41, it is preferable to perform only the inspection for the inspection item added as the new inspection item here.
[0097] (Step S45) Here, the same processing as in step S25 is performed. That is, the output unit 515 generates a diagnostic report from the test results obtained by the above processing and stores it in the storage unit 130. Then, this diagnostic report is output to the terminal device 70 of the service staff in response to a request from the terminal device 70 by the web application function.
[0098] As described above, the information processing apparatus according to the second embodiment includes an acquisition unit that acquires original inspection data from an image forming apparatus, and a second image analysis unit that executes a detection process for detecting, for the original inspection data, image unevenness with a new cycle other than the cycle inspected by predetermined inspection items including inspection items related to image unevenness with one or more specific cycles, which image unevenness occurs commonly in the plurality of original inspection data acquired from the plurality of image forming apparatuses. By including such a configuration, image unevenness with a new cycle can be detected with high accuracy.
[0099] The configurations of the information processing devices 50, 50b and the information processing system 500 including them described above are the main configurations described in explaining the features of the above-mentioned embodiments, but are not limited to the above configurations and can be modified in various ways within the scope of the claims. Furthermore, the configurations of the information processing devices 50, 50b and the information processing system 500 including them are not excluded. For example, the following modified configurations may be used.
[0100] (First Modification) The detection process (steps S22, S42) performed by the second image analysis unit 512 (or 514) may use device information, as in the modified example described below. The image forming devices 10 connected to the information processing device 50 may differ in model, but even if the model is the same, the configuration may not be uniform and may differ in minor respects. Furthermore, defects such as image unevenness may occur only between devices that share the same configuration. For example, an initial lot may be prone to image unevenness defects related to a certain inspection item, but in the next lot, a minor change to the configuration itself or a secondary effect of this change may eliminate the defect. Furthermore, image unevenness may occur if adjustment values (setting conditions) related to image formation and paper transport are improperly adjusted or are not correctly adjusted due to incompatibility with the firmware version.
[0101] Therefore, in the first modified example, in the new image unevenness detection process, image forming apparatuses 10 that share at least a portion of their device information are grouped together, and image unevenness that commonly occurs within the group is detected. In this case, by grouping based on multiple pieces of device information, one image forming apparatus 10 will belong to multiple groups. Specifically, new image unevenness is detected by performing the detection process of FIG. 9 multiple times for each group that shares device information. In this way, it is possible to detect image unevenness that occurs between image forming apparatuses 10 that share certain device information with greater accuracy than in the first and second embodiments.
[0102] (Second Modification) FIG. 17 is a subroutine flowchart showing the detection process of step S22 (or step S42) in the second modified example. In the first and second embodiments, the new image unevenness detection process is performed by rule-based control processing. However, the image unevenness detection process may also be performed using a trained model that has been machine-learned. This trained model can be trained by unsupervised learning using a data set that associates a large number of frequency analysis results (e.g., FIG. 11(c) and FIG. 12(c)) with device information as input. The trained model is stored in the storage unit 52. Applicable algorithms for unsupervised learning include the k-means method, Ward's method, and principal component analysis. The trained model can obtain an inspection frequency output by inputting device information.
[0103] (Step S501) Referring to FIG. 17, the second image analysis unit 512 (or 514) inputs device information into the trained model stored in the storage unit 52, and obtains an output of the inspection frequency.
[0104] (Step S502) The second image analysis unit 512 (or 514) performs frequency analysis on the profile data (or data after pre-processing) using the same process as in step S305 to obtain amplitude values for one or more new detection frequencies. Then, a judgment threshold is determined from the distribution of amplitude values. This ends the processing of the subroutine in FIG. 17, and the process returns to the processing in FIG. 8 (or FIG. 16). Even when using a machine-learned model in this way, the same effects as in the first or second embodiment can be obtained.
[0105] (Other variations) In the second embodiment described above, the first image analysis unit 513 (FIG. 15) of the information processing device 50b performs an inspection related to the third inspection item. The first image analysis unit 513 may be omitted, and all of this function may be performed by the image forming device 10. If all of this function is performed by the image forming device 10, the image forming device 10 may have the same function as the first image analysis unit 513. In this case, the information processing device 50b (second image analysis unit 514) specializes in detecting a new inspection item (an unknown frequency of image unevenness). After detecting the new inspection item, it distributes information about the inspection item (frequency, judgment threshold) to each image forming device 10. The image forming device 10 then adds the new inspection item to the first inspection item and subsequently performs periodic inspections using this inspection item. Note that, as in the first modification described above, if the inspection item depends on the device information, i.e., occurs only for specific device information, it may be distributed only to the image forming device 10 corresponding to that device information.
[0106] The information processing system 500 and the information processing device 50 according to the above-described embodiment may perform various processes using dedicated hardware circuits or a programmed computer. The programs may be provided by a computer-readable recording medium such as a USB memory or a DVD (Digital Versatile Disc)-ROM, or may be provided online via a network such as the Internet. In this case, the programs recorded on the computer-readable recording medium are typically transferred to and stored in a storage unit such as a hard disk. The programs may also be provided as standalone application software or may be incorporated into the software of a device as a function of the device. [Explanation of symbols]
[0107] 500 Information Processing Systems 10 Image forming device 11 Control section 111 First Image Analysis Unit 12 Storage section 13 Image forming unit 14 Paper feed transport section 15 Operation display section 16 Reading device 19 Communications Department 50 Information processing equipment 51 Control section 511 Acquisition Department 512 Second Image Analysis Unit 515 Output Section 52 Storage section 53 Communications Department 50b Information processing equipment 51b Control unit 511 Acquisition Department 513 First Image Analysis Unit 514 Second Image Analysis Unit 515 Output Section
Claims
1. An information processing device that is communicatively connected to one or more image forming devices that include an image forming unit, an image reading unit, and a first image analysis unit that detects image defects related to predetermined inspection items for read image data, an acquiring unit that acquires, from the image forming apparatus, original inspection data based on the read image data obtained by reading an image of a recording medium on which an image is formed by the image forming unit with the image reading unit; a second image analysis unit that performs an inspection on the original inspection data with inspection content different from that of the inspection performed by the first image analysis unit; Equipped with the predetermined inspection items to be inspected by the first image analysis unit include inspection of image unevenness of one or more specific periods; the second image analysis unit inspects image unevenness having a period other than the period inspected by the first image analysis unit; Information processing device.
2. The information processing apparatus according to claim 1 , wherein the second image analysis unit executes a detection process for detecting occurrence of image unevenness having a new cycle other than the cycle inspected by the first image analysis unit.
3. The information processing apparatus according to claim 2 , wherein the second image analysis unit detects periodic image unevenness that commonly occurs in the plurality of pieces of the inspection original data acquired from the plurality of image forming apparatuses in the detection process.
4. An information processing apparatus that is communicatively connected to a plurality of image forming apparatuses each having an image forming unit and an image reading unit, an acquiring unit that acquires, from the image forming apparatus, original inspection data based on read image data obtained by reading an image of a recording medium on which an image is formed by the image forming unit with the image reading unit; a second image analysis unit that executes a detection process for detecting image unevenness with a new period other than the period inspected by predetermined inspection items, including an inspection item related to image unevenness with one or more specific periods, in the plurality of pieces of inspection original data acquired from the plurality of image forming devices; and An information processing device comprising:
5. the image forming apparatus includes a first image analysis unit that detects defects in the image of the scanned image data related to the predetermined inspection items, The information processing apparatus according to claim 4 , wherein the second image analysis unit detects image unevenness having a new cycle other than the cycle inspected by the first image analysis unit based on the inspection item.
6. The information processing apparatus according to claim 4 , further comprising a first image analysis unit that detects defects in an image relating to the predetermined inspection item for the original inspection data.
7. the acquiring unit acquires, from the plurality of image forming devices, device information indicating at least one of a model, a hardware version, a software version, a setting condition, an installed part, and a usage history of the image forming devices; An information processing device as described in any one of claims 3 to 6, wherein the detection process of the second image analysis unit detects commonly occurring periodic image unevenness in the inspection source data obtained from image forming devices in which some or all of the device information is common among the multiple inspection source data.
8. the second image analysis unit performs a frequency analysis process on the original inspection data; 8. An information processing apparatus according to claim 3, wherein a signal amplitude or intensity judgment threshold for determining defects is determined based on a distribution of signal amplitude or intensity in a target period of the image unevenness detected by the detection process, the distribution being obtained by frequency analysis of the image unevenness that commonly occurs in a plurality of image forming devices.
9. 7. The information processing device according to claim 1, further comprising an output unit that integrates defects detected by the first image analysis unit and defects detected by the second image analysis unit, and, when multiple defects are detected, generates a report that assigns priority to the defects or displays them in order of priority.
10. 10. The information processing device according to claim 1, further comprising an output unit that integrates defects detected by the first image analysis unit and defects detected by the second image analysis unit, and generates a report that includes a composite image in which a marking image indicating the location where the defect occurred is superimposed on an image generated from the inspection source data.
11. an image forming apparatus including an image forming unit, an image reading unit, and a first image analysis unit that detects defects related to predetermined inspection items in the read image data; An information processing device according to any one of claims 1 to 5; An information processing system comprising:
12. An image analysis method executed by an information processing device communicatively connected to one or more image forming apparatuses each including an image forming unit, an image reading unit, and a first image analysis unit that detects image defects related to predetermined inspection items for read image data, a step (a) of acquiring, from the image forming apparatus, original inspection data based on the read image data obtained by reading, with the image reading unit, an image of a recording medium on which an image has been formed by the image forming unit; and (b) inspecting the original inspection data with inspection content different from that of the inspection performed by the first image analysis unit, the predetermined inspection items to be inspected by the first image analysis unit include inspection of image unevenness of one or more specific periods; In the step (b), an inspection is performed for image unevenness having a period other than the period inspected by the first image analysis unit. Image analysis methods.
13. 13. The image analysis method according to claim 12, wherein step (b) further includes a detection process for detecting occurrence of image unevenness having a new cycle other than the cycle inspected by the first image analysis unit.
14. The image analysis method according to claim 13 , wherein the detection process in step (b) detects periodic image unevenness that commonly occurs in the plurality of pieces of inspection original data acquired from the plurality of image forming devices.
15. An image analysis method executed by an information processing device communicatively connected to a plurality of image forming apparatuses each having an image forming unit and an image reading unit, a step (a) of acquiring, from the image forming apparatus, original inspection data based on read image data obtained by reading, with the image reading unit, an image of a recording medium on which an image has been formed by the image forming unit; and (b) executing a detection process for detecting image unevenness with a new period other than the period inspected by predetermined inspection items, including inspection items related to image unevenness with one or more specific periods, in the inspection source data acquired from the image forming devices, the image unevenness having a new period that commonly occurs.
16. In the step (a), device information indicating at least one of the model, hardware version, software version, setting conditions, installed parts, and usage history of the image forming devices is acquired from the plurality of image forming devices; The image analysis method of claim 14 or claim 15, wherein the detection process of step (b) detects commonly occurring periodic image unevenness in the inspection source data obtained from image forming devices that have some or all of the device information in common among the multiple inspection source data.
17. A control program for causing a computer to execute the image analysis method according to any one of claims 12 to 16.
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