Image processing method, image processing device, program, and conversion data

Abstract

Provided are: an image processing method in which pixel values of image data on which an output image is based are converted in accordance with trends of pixel values in read data of the output image; an image processing device; a program; and conversion data. The image processing method includes: acquiring first image data (S10); acquiring second image data (S12); for a second pixel value in the second image data, the second pixel value being associated with a first pixel value at the same pixel position in the first image data, creating conversion data for converting the first image data for each color each time the second image data are acquired, on the basis of a statistical value of a set of second pixel values for each first pixel value (S20); and using the conversion data to convert the first image data for each color (S22).

Description

Image processing method, image processing device, program, and conversion data

[0001] The present invention relates to an image processing method, an image processing device, a program, and converted data.

[0002] A print image inspection is known in which a print image is output by operating a printing device based on print data, and the print data is compared with scanned data of the print image to detect defects in the print image. Note that the print data in this specification may also be referred to as an original image, a master image, or the like.

[0003] Patent document 1 describes an inspection device that generates a master image from bitmap data received from an engine controller, generates a read image by reading a printed matter, which is a recording medium output from a print engine, and uses the master image and the read image to inspect the output result of the printed matter.

[0004] The device described in this document includes a color conversion processing unit that converts CMKY multi-value data into RGB color space. The color space conversion is performed by referring to a color conversion table that associates CMKY values ​​with RGB values. The device includes a color conversion table for each paper type, and performs color conversion for each paper type.

[0005] Japanese Patent Application Laid-Open No. 2006-102663 describes an image processing device that detects color mismatches between document image data and printed matter. The device described in this document detects color mismatches between a document image and a target printed matter based on statistical information calculated for each identical image signal value. In this device, the shape of a histogram calculated for each identical document image signal value is used as the statistical information calculated for each identical image signal value.

[0006] JP 2021-146594 A JP 2016-192742 A

[0007] However, although the device described in Patent Document 1 is provided with a color conversion table for each paper type, it is difficult to support all of the various types of paper used for printing. Also, storing color conversion tables corresponding to all of the various types of paper consumes a large amount of storage capacity.

[0008] The device described in Patent Document 2 requires a relatively large amount of calculations and a relatively long processing time for matching objects between an original image and a scanned image of a printed matter, converting color mismatches between the original image data and the printed matter into Lab values, etc. On the other hand, inspection of printed matter requires processing in a relatively short period of time.

[0009] The present invention has been made in consideration of the above circumstances, and aims to provide an image processing method, an image processing device, a program, and conversion data in which pixel values ​​of image data that form the basis of an output image are converted according to the tendency of pixel values ​​in the read data of the output image.

[0010] An image processing method according to a first aspect of the present disclosure is an image processing method that acquires first image data, acquires second image data generated by reading a first image from which the first image data is output, creates conversion data for converting first pixel values ​​in the first image data for each color based on statistical values ​​of a set of second pixel values ​​for each first pixel value, where the second pixel values ​​represent pixel values ​​for each pixel position in the second image data and are associated with first pixel values ​​representing pixel values ​​at the same pixel position in the first image data, and converts the first pixel values ​​of the first image data for each color using the conversion data created each time the second image data is acquired.

[0011] According to the image processing method of the first aspect of the present disclosure, first pixel values ​​in the first image data for each color are converted using conversion data generated based on the statistics of the set of second pixel values, thereby converting the first image data to reflect the statistics of the set of second pixel values.

[0012] Furthermore, the first image data is converted each time the second image data is acquired, thereby enabling the first image data to be converted in accordance with each of the plurality of second image data.

[0013] The first image data may include one or more colors. The color information included in the first image data may be a color representation based on additive color mixing or a color reproduction based on subtractive color mixing.

[0014] The statistical value may be calculated by applying a statistical operation to a plurality of second pixel values ​​corresponding to the first pixel value.

[0015] An image processing method according to a second aspect may be the image processing method of the first aspect, further comprising creating a first pixel value map representing first pixel values ​​for each pixel position in the first image data, creating a second pixel value map representing second pixel values ​​for each pixel position in the second image data, and using the first pixel value map and the second pixel value map to associate the second pixel values ​​with the first pixel values ​​at the same pixel positions in the first image data.

[0016] According to this aspect, when associating a second pixel value with a first pixel value at the same pixel position in the first image data, a second pixel value for each pixel position in the second pixel value map can be associated with a first pixel value for each pixel position in the first pixel value map.

[0017] A preferred embodiment is one in which resolution conversion is performed to match the resolution of the first image data with the resolution of the second image data.

[0018] An image processing method according to a third aspect may be the image processing method according to the first or second aspect, wherein the statistical value is an arithmetic mean value or a median value.

[0019] According to this aspect, a relatively short process is applied to obtain statistics of the second pixel values ​​that are relatively reliable.

[0020] An image processing method according to a fourth aspect may be an image processing method according to any one of the first to third aspects, in which first image data containing information on multiple colors is obtained, and second pixel values ​​for each pixel position in second image data for each color are associated with first pixel values ​​for the same pixel position in first image data of the same color as the second image data.

[0021] According to this aspect, when the first image data includes information on a plurality of colors, the correspondence between the first pixel values ​​of the first image data and the second pixel values ​​of the second image data is performed for each of the same colors.

[0022] An image processing method according to a fifth aspect may be an image processing method according to any one of the first to third aspects, in which first image data containing information on multiple colors is obtained, and second pixel values ​​for each pixel position in second image data for each color are associated with first pixel values ​​of the first image data containing information on multiple colors.

[0023] According to this aspect, it is possible to correspond a first pixel value of first image data that includes information on multiple colors to a second pixel value of second image data that reflects information on a color different from the color of interest in the first image data.

[0024] An image processing method according to a sixth aspect may be an image processing method according to any one of the first to fifth aspects, in which a lookup table is created as conversion data to convert first pixel values ​​of first image data for each color, and the lookup table is used to convert the first pixel values ​​of the first image data to create reference data for inspecting defects in an output image of the first image data.

[0025] According to this aspect, a lookup table based on statistics of the second pixel values ​​for each first pixel value is created for each color of the first image data, and the pixel values ​​of the first image data are converted for each color, thereby completing the conversion of the first pixel values ​​of the first image data in a relatively short process.

[0026] The image processing method according to the seventh aspect may be an image processing method according to any one of the first to sixth aspects, in which print data that serves as the original for printing is obtained as the first image data, and read data for each color of the printed image printed by applying the print data is obtained as the second image data.

[0027] According to this aspect, the first pixel values ​​of the print data are converted so that the tendency of the second pixel values ​​of the read data of the print image is reflected.

[0028] An image processing device according to an eighth aspect of the present disclosure includes one or more processors and one or more memories storing a program including one or more instructions executed by the one or more processors, wherein the one or more processors execute the program to acquire first image data, acquire second image data generated by reading a first image from which the first image data is output, create conversion data for converting first pixel values ​​in the first image data for each color based on statistical values ​​of a set of second pixel values ​​for each first pixel value, the second pixel values ​​representing pixel values ​​for each pixel position in the second image data and corresponding to first pixel values ​​representing pixel values ​​at the same pixel position in the first image data, and convert the first pixel values ​​of the first image data for each color using the conversion data created each time the second image data is acquired.

[0029] According to the image processing device according to the eighth aspect of the present disclosure, it is possible to obtain the same effects as the image processing method according to the first aspect of the present disclosure. The constituent elements of the image processing methods according to the second to seventh aspects can be applied to the constituent elements of the image processing device according to the other aspects.

[0030] A program according to a ninth aspect of the present disclosure is a program that enables a computer having one or more processors and one or more memories storing a program including one or more instructions executed by the one or more processors to realize the following functions: acquiring first image data; acquiring second image data generated by reading a first image from which the first image data is output; creating conversion data that converts first pixel values ​​in the first image data for each color based on statistical values ​​of a set of second pixel values ​​for each first pixel value, where the second pixel values ​​represent pixel values ​​for each pixel position in the second image data and are associated with first pixel values ​​representing pixel values ​​at the same pixel position in the first image data; and converting the first pixel values ​​of the first image data for each color using the conversion data created each time the second image data is acquired.

[0031] According to the program of the ninth aspect of the present disclosure, it is possible to obtain the same effects as the image processing method of the first aspect of the present disclosure. The constituent elements of the image processing methods of the second to seventh aspects can be applied to the constituent elements of the program of the other aspects.

[0032] The conversion data according to the tenth aspect of the present disclosure is second pixel values ​​representing pixel values ​​for each pixel position in second image data generated by reading a first image output based on first image data, and is conversion data that converts the first pixel values ​​in the first image data for each color based on the statistical value of the set of second pixel values ​​for each first pixel value for second pixel values ​​associated with first pixel values ​​representing pixel values ​​at the same pixel position in the first image data.

[0033] According to the conversion data of the tenth aspect of the present disclosure, it is possible to obtain the same effects as the image processing method of the first aspect of the present disclosure. The constituent elements of the image processing methods of the second to seventh aspects can be applied to the constituent elements of the conversion data of the other aspects.

[0034] According to the present invention, the first pixel values ​​in the first image data for each color are converted using conversion data generated based on the statistics of the set of second pixel values, thereby converting the first image data so that the statistics of the set of second pixel values ​​are reflected.

[0035] Furthermore, the first image data is converted each time the second image data is acquired, thereby enabling the first image data to be converted in accordance with each of the plurality of second image data.

[0036] FIG. 1 is a functional block diagram showing the electrical configuration of an image processing apparatus according to an embodiment. FIG. 2 is a schematic diagram showing a specific example of a pixel value map. FIG. 3 is a schematic diagram showing a specific example of a pixel value correspondence set and a specific example of a statistical value. FIG. 4 is a schematic diagram of reference image data. FIG. 5 is a schematic diagram showing a first example of pixel values ​​in print data. FIG. 6 is a schematic diagram showing a second example of pixel values ​​in print data. FIG. 7 is a schematic diagram showing an example of pixel values ​​in print data according to the second example. FIG. 8 is a schematic diagram showing a third example of pixel values ​​in print data. FIG. 9 is a schematic diagram showing an example of pixel values ​​in print data according to the third example. FIG. 10 is a schematic diagram showing a fourth example of pixel values ​​in print data. FIG. 11 is a schematic diagram showing an example of pixel values ​​in print data according to the fourth example. FIG. 12 is a schematic diagram showing a fifth example of pixel values ​​in print data. FIG. 13 is a schematic diagram showing a sixth example of pixel values ​​in print data. FIG. 14 is a schematic diagram showing an example of pixel values ​​in print data according to the sixth example. Fig. 15 is a block diagram showing the hardware configuration of the image processing device shown in Fig. 1. Fig. 16 is a flowchart showing the procedure of an inspection method according to an embodiment. Fig. 17 is a block diagram showing an example of the configuration of a printing system including the image processing device shown in Fig. 1. Fig. 18 is a functional block diagram showing the electrical configuration of the printing system shown in Fig. 17.

[0037] Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In this specification, identical components are designated by the same reference numerals, and duplicate descriptions will be omitted where appropriate. Furthermore, when multiple components are listed in the following embodiments, it can be interpreted as including at least one of the multiple components.

[0038] 1 is a functional block diagram showing the electrical configuration of an image processing apparatus according to an embodiment. The image processing apparatus 10 shown in the figure operates a printing apparatus based on print data to generate reference image data for inspection comparison, which is used to inspect defects in printed images.

[0039] In a defect inspection of a printed image, the image data to be inspected is compared with the reference image data, and defects in the printed image are extracted based on the comparison results. An example of the image data to be inspected is scanned image data generated by reading the printed image using a reading device such as a scanner.

[0040] When printing is performed, print data having color information of ink colors CMYK is transferred to the printer. The CMYK print data is converted into color information of scanned image data. An example of the color information of scanned image data is RGB. Note that C, M, Y, and K represent cyan, magenta, yellow, and black, respectively, and R, G, and B represent red, green, and blue, respectively.

[0041] To convert color information from CMYK to RGB, a color conversion table, which is a lookup table in which CMYK values ​​correspond to RGB values, is referenced. That is, to convert color information, a lookup table that shows the correspondence between color information is created in advance and used.

[0042] The conversion of color information may involve calculating conversion values ​​for multiple pixel positions in the source image and the destination image that are the target of color information conversion. Note that the lookup table may be referred to as Lut, which is an abbreviation of lookup table.

[0043] However, in the past, the conditions used to match the color information of print data and scanned image data were fixed, and if the printing conditions, such as the print medium used for printing, changed, the color development of the printed image could change. Furthermore, if the printing conditions changed, the scanning conditions for scanning the printed image could also change. As a result, when simply comparing the print data with the converted color information and the scanned image data, many differences arise between the print data and the scanned image data. The device described in Patent Document 1 creates a lookup table for each paper type, but it is difficult to support all of the wide variety of print media. Furthermore, storing many lookup tables corresponding to many print media consumes a large amount of memory.

[0044] The image processing device 10 according to the embodiment corrects the pixel values ​​of the print data for each color according to the trend of the pixel values ​​of the scan image data each time scan image data is acquired, and generates reference image data for each scan image data. This generates reference image data that reflects the trend of the pixel values ​​for each color of the multiple scan image data, and suppresses a decrease in the accuracy of defect inspection of print images caused by changes in printing conditions, photographing conditions, etc. in the scan image data.

[0045] The image processing device 10 includes a print data acquisition unit 12 that acquires print data to be transferred to a printer. The print data acquisition unit 12 may perform color conversion of the acquired print data. For example, when CMYK print data is transferred to a printer, the CMYK print data may be color converted to RGB print data. The image processing device 10 may also include a color conversion processing unit that performs color conversion of the print data.

[0046] The image processing device 10 includes a scan image data acquisition unit 14. The scan image data acquisition unit 14 acquires scan image data used for defect inspection of a printed image. The scan image data acquisition unit 14 may acquire the scan image data from a scanner that reads the printed image, or may acquire the scan image data from an inspection device that inspects the printed image for defects.

[0047] The image processing device 10 includes a pixel value map creation unit 16. The pixel value map creation unit 16 creates a print pixel value map that represents pixel values ​​for each pixel position in the print data, and a scan pixel value map that represents pixel values ​​for each pixel position in the scan image data.

[0048] The pixel value map creation unit 16 aligns the print data and the scanned image data and converts them to the same resolution. The alignment of the print data and the scanned image data can include translation, rotation, enlargement, and reduction in any direction.

[0049] Relatively high effects can be achieved by calculating the correlation value between the print data that has been aligned with the scan image data and the scan image data, and repeatedly correcting the position and calculating the correlation value so that the correlation value becomes relatively high, thereby improving the accuracy of alignment between the print data and the scan image data.

[0050] When converting the resolution of print data and scanned image data, the resolution of the scanned image data may be converted based on the resolution of the print data, the resolution of the print data may be converted based on the resolution of the scanned image data, or the print data and scanned image data may be converted to a specified resolution different from their original resolutions.

[0051] The image processing device 10 may also include, as components separate from the pixel value map creation unit 16, an alignment processing unit that aligns the print data and the scanned image data, and a resolution conversion unit that converts the resolution of the print data and the scanned image data.

[0052] The image processing device 10 includes a pixel value correspondence set creation unit 18. The pixel value correspondence set creation unit 18 creates a pixel value correspondence set, which is a set of pixel values ​​in the scanned image data that correspond to each pixel value in the print data, based on the print pixel value map and the scan pixel value map.

[0053] The image processing device 10 includes a statistical value calculation unit 20. The statistical value calculation unit 20 calculates a statistical value for a set of multiple pixel values ​​in the scanned image data for each pixel value of the print data based on the pixel value correspondence set. The statistical value may be an arithmetic mean value, a median value, or the like.

[0054] The image processing device 10 includes a pixel value conversion lookup table creation unit 22. The pixel value conversion lookup table creation unit 22 creates a pixel value conversion lookup table to be applied to the conversion process of pixel values ​​of the print data, using statistical values ​​of pixel values ​​of the scanned image data for each pixel value of the print data.

[0055] A pixel value conversion lookup table is created for each color of the print data. For example, if the print data is RGB, a pixel value conversion lookup table for R, a pixel value conversion lookup table for G, and a pixel value conversion lookup table for B are created.

[0056] The image processing apparatus 10 includes a pixel value conversion unit 24. The pixel value conversion unit 24 performs conversion processing on pixel values ​​of print data using a pixel value conversion lookup table, and generates reference image data for inspection comparison.

[0057] For example, using an R pixel value conversion lookup table, the R pixel value at each pixel position of the print data is converted, and the R pixel value at each pixel position of the reference image data is obtained. For B and G, the same process as for R is performed, and the G pixel value and B pixel value at each pixel position of the reference image data are obtained. The reference image data is transferred to the inspection device 30.

[0058] The inspection device 30 includes a reference image data acquisition unit 32, an inspection object image data acquisition unit 34, a comparison unit 36, and a defect extraction unit 38. The reference image data acquisition unit 32 acquires reference image data transferred from the image processing device 10. The inspection object image data acquisition unit 34 acquires scan image data as inspection object image data.

[0059] The comparison unit 36 ​​compares the reference image data with the scanned image data. The comparison unit 36 ​​may align the reference image data with the scanned image data and adjust the resolution between the reference image data and the scanned image data. The processing unit that performs the alignment and the processing unit that performs the resolution adjustment may be provided in the inspection device 30 as independent processing units separate from the components of the inspection device 30, or may be provided in components separate from the comparison unit 36, such as the reference image data acquisition unit 32 and the inspection object image data acquisition unit 34.

[0060] The defect extraction unit 38 extracts defects in the printed image based on the comparison result between the reference image data and the scanned image data. The defect extraction unit 38 may generate defect information such as the position and degree of the defect in the printed image, and output the defect information.

[0061] Note that the print data described in the embodiment is an example of first image data, and the print image described in the embodiment is an example of the first image. The scanned image data described in the embodiment is an example of second image data. The print image described in the embodiment is an example of an output image, and the reference image data described in the embodiment is an example of reference data.

[0062] [Specific Example of Pixel Value Map] Figure 2 is a schematic diagram showing a specific example of a pixel value map. The print pixel value map PM shown in the figure corresponds to print data for any one color in print data for multiple colors, and represents pixel values ​​for one color at each pixel position. The print pixel value map PM shown in Figure 2 corresponds to print data for R in RGB print data.

[0063] Similar to the R print pixel value map PM shown in Figure 2, a G print pixel value map corresponding to the G print data in the RGB print data, and a B print pixel value map corresponding to the B print data in the RGB print data are created.

[0064] The scan pixel value map SM shown in Figure 2 represents any one of the multiple colors in the scanned image data, and represents pixel values ​​for each pixel position for the same color as the print pixel value map PM. A scan pixel value map SM is created for each color that makes up the scanned image data. Figure 2 shows integers between 0 and 255 as examples of pixel values ​​in the print pixel value map PM and the scan pixel value map SM.

[0065] There is a one-to-one correspondence between pixel positions in the print pixel value map PM and pixel values ​​in the scan pixel value map SM. For example, 11 and the pixel position P in the scan pixel value map SM 21 Similarly, the pixel position P 12 and the pixel position P in the scan pixel value map SM 22 is the same pixel position, and is the pixel position P 13 and the pixel position P in the scan pixel value map SM 23means the same pixel position.

[0066] Note that the pixel values ​​of the print data described in the embodiment are an example of first pixel values, and the pixel values ​​of the scanned image data described in the embodiment are an example of second pixel values. Also, the print pixel value map PM described in the embodiment is an example of a first pixel value map, and the scan pixel value map SM described in the embodiment is an example of a second pixel value map.

[0067] 3 is a schematic diagram showing a specific example of a pixel value correspondence set and a specific example of a statistical value. The pixel value correspondence set SE is shown in a table format. The statistical value SV of the set of pixel values ​​in the scanned image data is also shown.

[0068] The pixel value correspondence set SE shown in Figure 3 is created as a set of one or more pixel values ​​of the scanned image data for each pixel value of the print data, by corresponding pixel values ​​at each pixel position in the scanned pixel value map SM shown in Figure 2 to pixel values ​​at the same pixel position in the printed pixel value map PM.

[0069] For example, when the pixel value of the print data is 32, the pixel position P 21 The pixel value is 28, and the pixel position is P 22 28, which is the pixel value of the pixel at the pixel position P 23 In this way, all pixel values ​​applied to the print data are associated with pixel values ​​at the same pixel positions in the scan pixel value map SM as in the print pixel value map PM.

[0070] 3 illustrates a set of pixel values ​​for any one of the one or more colors that make up the scanned image data. A pixel value correspondence set SE is created for all colors that make up the scanned image data.

[0071] 3 illustrates an example of a statistical value SV of a set of pixel values ​​in scanned image data, which may be a mean value and a median value. The mean value may be an arithmetic mean value. The statistical value SV may be a value other than the mean value and the median, such as a standard deviation.

[0072] [Creating a pixel value conversion lookup table] Based on the statistical value SV of the set of pixel values ​​in the scanned image data for each pixel value of the print data shown in Figure 3, a pixel value conversion lookup table is created that is applied when converting print data to reference image data.

[0073] The pixel value conversion lookup table defines conversion data for converting pixel values ​​of print data based on a statistical value SV of a set of pixel values ​​in the scanned image data for each pixel value of the print data. For example, a pixel value of 30 in the print data is converted to 28, which is the average value of the set of pixel values ​​in the scanned image data. A pixel value conversion lookup table is created for each color of the print data.

[0074] 4 is a schematic diagram of the reference image data RI. The pixel values ​​of 32, 80, 96, 128, 150, and 192 in the print data shown in FIG. 3 are converted to the median values ​​of the set of pixel values ​​in the scanned image data, 28, 82, 98, 130, 145, and 182, respectively, to generate the reference image data RI.

[0075] Because the area of ​​a defect in a printed image is small compared to the overall area of ​​the printed image, it is unlikely that the pixel value of the defect in the printed image matches the statistical value SV of the set of pixel values ​​in the scanned image data. If the pixel value of the defect in the printed image matches the statistical value SV of the set of pixel values ​​in the scanned image data, the pixel values ​​in the normal area of ​​the printed image are determined to be abnormal values. In this way, the presence or absence of a defect can be identified even if the position of the defect in the printed image cannot be identified.

[0076] In converting the print data into reference image data, a pixel value correspondence set SE, which is a set of pixel values ​​at the same positions as the print data, is created for the scanned image data, a statistical value SV of the set of pixel values ​​in the scanned image data for each pixel value of the print data is calculated, a pixel value conversion lookup table is created based on the statistical value SV, and the print data is converted using the pixel value conversion lookup table. This series of processes is completed in a relatively short time.

[0077] Furthermore, since a pixel value conversion lookup table is created for each color that constitutes the scanned image data, there is no need to consider Lab or other correlations between the colors of the scanned image data, enabling high-speed processing.

[0078] [Specific example of pixel values ​​of print data] [Example of pixel values ​​for each RGB] Fig. 5 is a schematic diagram showing a first example of pixel values ​​in print data. In the drawing, the correspondence between print data R and scanned image data R, the correspondence between print data G and scanned image data G, and the correspondence between print data B and scanned image data B are schematically illustrated in a graph format. The same applies to the graphs illustrated in Figs. 6, 8, 10, 12, and 13.

[0079] If the print data is RGB and the scan image data is RGB, a pixel value conversion lookup table is created for each of R, B, and G that converts the pixel values ​​of the print data according to the correspondence between the print data and the scan image data.

[0080] Figure 5 illustrates pixel value conversion lookup table LutR that converts pixel values ​​of print data R, pixel value conversion lookup table LutG that converts pixel values ​​of print data G, and pixel value conversion lookup table LutB that converts pixel values ​​of print data B.

[0081] [Example of pixel values ​​in which all RGB information is used] Figure 6 is a schematic diagram showing a second example of pixel values ​​in print data. The pixel values ​​of the print data may include information on two or more colors. Figure 6 shows an example in which all RGB information is used as pixel values ​​of the print data, and an example in which information on three colors is included.

[0082] 7 is a schematic diagram showing an example of pixel values ​​of print data according to Example 2. The diagram shows an example in which 8-bit data is applied as the pixel value of each color, which are the pixel values ​​of R, G, and B at an arbitrary pixel position used in the print data.

[0083] In print data, an example of pixel values ​​in which all RGB information is used is when the pixel values ​​of 8-bit data for each color are concatenated and treated as 24-bit data. When creating an R pixel value conversion lookup table LutR, the 8 bits from the most significant bit may be used as the R pixel value, the 8 bits from the 9th bit to the 16th bit may be used as the G pixel value, and the 8 bits from the 17th bit to the most significant bit may be used as the B pixel value. The pixel value of the 24-bit data generated by concatenating the pixel values ​​of the 8-bit data for each color shown in Figure 7 is expressed as 8405184 when decimal notation is applied.

[0084] Furthermore, when a G pixel value conversion lookup table LutG is created, the pixel values ​​of the print data may be 24-bit data arranged in the order of G pixel value, B pixel value, and R pixel value from the most significant bit.

[0085] Similarly, when a pixel value conversion lookup table LutB for B is created, the pixel values ​​of the print data may be 24-bit data arranged in the order of the B pixel value, the R pixel value, and the G pixel value from the most significant bit.

[0086] In other words, the pixel value of the color of interest may be placed on the most significant bit side, and the pixel values ​​of colors different from the color of interest may be arranged in order of relatively high correlation with the color of interest, thereby creating pixel values ​​for print data that include information on all colors.

[0087] [Example of pixel values ​​using part of RGB information] Figure 8 is a schematic diagram showing a third example of pixel values ​​in print data. This figure illustrates an example in which part of the information of a color different from the color of interest is used. Figure 8 also illustrates a case in which, when focusing on R, G information is used, but B information is not used.

[0088] Figure 8 also illustrates a case where, when focusing on G, information on B is used but information on R is not used, and a case where, when focusing on B, information on R is used but information on G is not used.

[0089] 9 is a schematic diagram showing an example of pixel values ​​of print data according to Example 3. The diagram illustrates an example in which a G pixel value, also 8-bit data, is concatenated with an R pixel value, also 8-bit data, as the pixel value of the print data. The diagram also illustrates a B pixel value that is not used in the print data pixel value as a blank.

[0090] In print data, an example of a pixel value that uses part of the RGB information is 16-bit data in which, when focusing on R, the R pixel value and the G pixel value are arranged in that order from the most significant bit. The pixel value shown in Fig. 8 is expressed as 32832 when decimal notation is applied.

[0091] 10 is a schematic diagram showing a fourth example of pixel values ​​in print data. This figure illustrates another example in which part of the information of a color different from the color of interest is used. In FIG. 10, when focusing on R, part of the information of G and part of the information of B are used.

[0092] Figure 10 also illustrates a case where part of the B information and part of the R information are used when focusing on G, and a case where part of the R information and part of the G information are used when focusing on B.

[0093] 11 is a schematic diagram showing an example of pixel values ​​of print data according to Example 4. The figure shows an example in which the pixel value of print data is obtained by concatenating the upper four bits of the pixel value of a G pixel (8-bit data) and the upper four bits of the pixel value of a B pixel (8-bit data) with the pixel value of an R pixel (8-bit data). The pixel value shown in FIG. 11 is expressed as 32844 using a decimal system.

[0094] The aspect in which part of the information of a color different from the color of interest is used as the pixel value of the color of interest can be expected to be effective in cases where a color different from the color of interest has an effect at the same pixel position, such as when 100% blue B and 100% composite black B do not generate the same image for the B channel of scanned image data.

[0095] [Example in which CMYK is applied to print data] Figure 12 is a schematic diagram showing a fifth example of pixel values ​​in print data. This figure illustrates a case in which the print data is CMYK and the scanned image data is RGB. This figure also illustrates an example in which all CMYK information is used.

[0096] 13 is a schematic diagram showing a sixth example of pixel values ​​in print data. This diagram illustrates an example in which partial information of CMYK is used. For example, if the color of interest is R, the M pixel values ​​and Y pixel values ​​of the print data, which have a relatively strong correlation with R, are used, and partial C pixel values ​​and partial K pixel values ​​of the print data, which have a relatively weak correlation with R, are used to create the R pixel value conversion lookup table LutR.

[0097] When the color of interest is G, the C pixel values ​​and Y pixel values ​​of the print data, which have a relatively strong correlation with G, are used, and part of the M pixel values ​​and part of the K pixel values ​​of the print data, which have a relatively weak correlation with G, are used to create a G pixel value conversion lookup table LutG.

[0098] When the color of interest is B, the C pixel values ​​and M pixel values ​​of the print data, which have a relatively strong correlation with B, are used, and part of the Y pixel values ​​and part of the K pixel values ​​of the print data, which have a relatively weak correlation with G, are used to create the G pixel value conversion lookup table LutB.

[0099] 14 is a schematic diagram showing an example of pixel values ​​of print data according to Example 6. In this diagram, when the color of interest is B, the pixel value of C (8-bit data), the pixel value of M (8-bit data), the most significant four bits of the pixel value of Y (8-bit data), and the most significant four bits of the pixel value of K (8-bit data) are concatenated to represent the pixel value of the print data as 24-bit data.

[0100] 12 to 14 show an example in which the scanned image data has RGB color information, but the color information of the scanned image data may be CMYK, or may be color information when a complementary color scanner is used.

[0101] [Hardware Configuration of Image Processing Device] Fig. 15 is a block diagram showing the hardware configuration of the image processing device shown in Fig. 1. The image processing device 10 shown in Fig. 1 is implemented by a computer including one or more processors and one or more memories that store programs including instructions executed by the one or more processors.

[0102] The computer applied to the image processing device 10 may be a personal computer or a workstation. The computer may be a virtual machine. The image processing device 10 may be configured using multiple computers.

[0103] The image processing device 10 includes a processor 52 , a computer-readable medium 54 , a communication interface 56 , an input / output interface 58 , and a bus 60 .

[0104] The processor 52 includes a CPU. The processor 52 may include a GPU. Note that CPU is an abbreviation for Central Processing Unit, and GPU is an abbreviation for Graphics Processing Unit.

[0105] The processor 52 is connected to the computer-readable medium 54, the communication interface 56, and the input / output interface 58 via a bus 60. An input device 66 and a display 68 are connected to the image processing apparatus 10 via the input / output interface 58.

[0106] The image processing apparatus 10 realizes various functions by the processor 52 executing a program stored in a computer-readable medium 54. The term "program" is synonymous with the term "software."

[0107] The computer-readable medium 54 includes a memory 62 serving as a main storage device and a storage 64 serving as an auxiliary storage device. The computer-readable medium 54 may be a semiconductor memory, a hard disk drive, a solid-state drive, or the like. The computer-readable medium 54 may be any combination of multiple devices.

[0108] A hard disk drive may be referred to as an HDD, which is an abbreviation of the English term Hard Disk Drive, and a solid state drive may be referred to as an SSD, which is an abbreviation of the English term Solid State Drive.

[0109] The image processing device 10 communicates data with external devices via a communication interface 56. The communication interface 56 may comply with various standards, such as USB. The communication format of the communication interface 56 may be either wired communication or wireless communication. USB is an abbreviation for Universal Serial Bus and is a registered trademark.

[0110] The processor 52 is connected to an input device 66 and a display 68 via an input / output interface 58. The input device 66 is implemented by input devices such as a keyboard and a mouse. The display 68 displays various types of information applied to the image processing device 10.

[0111] The display 68 is used as part of the GUI when receiving input from the input device 66. The display 68 is not limited to one, and may be in the form of a multi-display having a plurality of displays.

[0112] The display 68 may be a liquid crystal display, an organic EL display, a projector, or any combination of multiple devices. The "EL" in the organic EL display is an abbreviation for Electro-Luminescence.

[0113] The memory 62 of the computer-readable medium 54 stores a print data acquisition program 70, a scanned image data acquisition program 72, a pixel value map creation program 74, a pixel value correspondence set creation program 76, a statistical value calculation program 78, a pixel value conversion lookup table creation program 80, and a pixel value conversion program 82, which are executed by the processor 52.

[0114] The print data acquisition program 70 is applied to the print data acquisition unit 12 shown in Fig. 1 and realizes the function of acquiring print data. The scan image data acquisition program 72 is applied to the scan image data acquisition unit 14 and realizes the function of acquiring scan image data. The pixel value map creation program 74 is applied to the pixel value map creation unit 16 and realizes the function of creating the print pixel value map PM and the scan pixel value map SM shown in Fig. 2.

[0115] The pixel value correspondence set creation program 76 is applied to the pixel value correspondence set creation unit 18, and realizes the function of creating the pixel value correspondence set SE shown in Fig. 3. The statistical value calculation program 78 is applied to the statistical value calculation unit 20, and realizes the function of calculating the statistical value SV of the set of pixel values ​​in the scanned image data shown in Fig. 3.

[0116] The pixel value conversion lookup table creation program 80 is applied to the pixel value conversion lookup table creation unit 22, and realizes the function of creating a pixel value conversion lookup table for each color. The pixel value conversion program 82 is applied to the pixel value conversion unit 24, and realizes the function of converting the pixel values ​​of the print data for each color using the pixel value conversion lookup table.

[0117] The various programs stored in the computer-readable medium 54 include one or more instructions. The computer-readable medium 54 stores various data, various parameters, and the like.

[0118] Examples of the hardware structure of the processor 52 include a CPU, a GPU, a programmable logic device (PLD), and an application specific integrated circuit (ASIC). The CPU is a general-purpose processor that executes programs and functions as various functional units. The GPU is a processor specialized for image processing.

[0119] A PLD is a processor whose electrical circuit configuration can be changed after the device is manufactured. An example of a PLD is an FPGA (Field Programmable Gate Array). An ASIC is a processor with dedicated electrical circuitry designed specifically to perform a specific process.

[0120] A processing unit may be configured with one of these various processors, or may be configured with two or more processors of the same or different types. Examples of combinations of various processors include a combination of one or more FPGAs and one or more CPUs, and a combination of one or more FPGAs and one or more GPUs. Another example of a combination of various processors is a combination of one or more CPUs and one or more GPUs.

[0121] A single processor may be used to configure multiple functional units. An example of using a single processor to configure multiple functional units is a configuration in which a single processor is configured by applying a combination of one or more CPUs and software, such as a SoC (System On a Chip) that is typified by a computer such as a client or server, and this processor operates as multiple functional units.

[0122] Another example of using one processor to configure multiple functional units is to use a processor that uses one IC chip to realize the functions of an entire system including multiple functional units. Note that IC is an abbreviation for Integrated Circuit.

[0123] In this way, the various functional units are configured as hardware structures using one or more of the various processors described above.More specifically, the hardware structures of the various processors described above are electric circuits (circuitry) that combine circuit elements such as semiconductor elements.

[0124] When alignment processing, resolution conversion processing, and color conversion processing are performed in the image processing device 10, the memory 62 may store an alignment program that realizes the alignment function, a resolution conversion program that realizes the resolution conversion function, and a color conversion program that realizes the color conversion function.

[0125] 1 is implemented as a computer having one or more processors and one or more memories for storing a program including one or more instructions executed by the one or more processors, similar to the image processing device 10. The computer implemented in the image processing device 10 and the computer implemented in the inspection device 30 may be partially or entirely common to each other.

[0126] [Procedure of Inspection Method According to Embodiment] Fig. 16 is a flowchart showing the procedure of the inspection method according to the embodiment. In a print data acquisition step S10, the print data acquisition unit 12 shown in Fig. 1 acquires print data. After the print data acquisition step S10, the process proceeds to a scanned image data acquisition step S12.

[0127] In the scan image data acquisition step S12, the scan image data acquisition unit 14 acquires scan image data. After the scan image data acquisition step S12, the process proceeds to the pixel value map creation step S14. The scan image data acquisition step S12 may be executed in parallel with the print data acquisition step S10, or the order of the scan image data acquisition step S12 and the print data acquisition step S10 may be reversed.

[0128] In the pixel value map creation step S14, the pixel value map creation unit 16 creates a print pixel value map PM from the print data acquired in the print data acquisition step S10, and also creates a scan pixel value map SM from the scan image data acquired in the scan image data acquisition step S12. After the pixel value map creation step S14, the process proceeds to a pixel value correspondence set creation step S16.

[0129] In the pixel value correspondence set creation step S16, the pixel value correspondence set creation unit 18 uses the print pixel value map PM and the scan pixel value map SM to create the pixel value correspondence set SE shown in Fig. 3. After the pixel value correspondence set creation step S16, the process proceeds to the statistical value calculation step S18.

[0130] In the statistical value calculation step S18, the statistical value calculation unit 20 calculates a statistical value SV of the set of pixel values ​​of the scanned image data for each pixel value in the print data using the pixel value correspondence set SE. After the statistical value calculation step S18, the process proceeds to the pixel value conversion lookup table creation step S20.

[0131] In the pixel value conversion lookup table creation step S20, the pixel value conversion lookup table creation unit 22 uses the statistical value SV calculated in the statistical value calculation step S18 to create a pixel value conversion lookup table to be applied to the conversion process of pixel values ​​of the print data. As examples of pixel value conversion lookup tables for each color of the print data, pixel value conversion lookup table LutR, pixel value conversion lookup table LutG, and pixel value conversion lookup table LutB for each color are shown in Figure 5, etc. After the pixel value conversion lookup table creation step S20, the process proceeds to the pixel value conversion step S22.

[0132] In the pixel value conversion step S22, the pixel value conversion unit 24 converts the pixel values ​​of the print data for each color of the print data using the pixel value conversion lookup table created in the pixel value conversion lookup table creation step S20 to create reference image data. After the pixel value conversion step S22, the process proceeds to the comparison step S24.

[0133] The steps of the inspection method, from the print data acquisition step S10 to the pixel value conversion step S22, are understood to be steps of the image processing method according to the embodiment. Each step included in the image processing method according to the embodiment is executed, and reference image data is generated from the print data.

[0134] In the comparison step S24, the comparison unit 36 ​​of the inspection device 30 shown in FIG. 1 compares the reference image data with the scanned image data, which is the image to be inspected. After the comparison step S24, the process proceeds to the defect extraction step S26. Before the comparison step S24 is performed, a reference image data acquisition step for acquiring the reference image data created in the pixel value conversion step S22 and a scanned image data acquisition step for acquiring scanned image data, which is the image to be inspected, may be performed. After the comparison step S24, the process proceeds to the defect extraction step S26.

[0135] In the defect extraction step S26, the defect extraction unit 38 extracts defects in the printed image based on the comparison result between the reference image data and the scanned image data derived in the comparison step S24. After the defect extraction step S26, the process proceeds to the inspection completion determination step S28.

[0136] In the inspection end determination step S28, the inspection device 30 determines whether or not the end conditions for the defect inspection of the printed image are satisfied. Examples of the end conditions for the defect inspection of the printed image include receiving a signal indicating the end of inspection of a specified number of printed images or a forced end.

[0137] In the inspection end determination step S28, if it is determined that the end conditions for the defect inspection of the printed image are not satisfied, the determination is No. If the determination is No, the defect inspection of the printed image continues, and the process proceeds to the print data change determination step S30.

[0138] In the print data change determination step S30, it is determined whether the print data will be changed. If it is determined that the print data will not be changed in the print data change determination step S30, the determination is No. If the determination is No, the process proceeds to the scan image data acquisition step S12, where scan image data for the next print image to be inspected is acquired, and each step from the scan image data acquisition step S12 to the print data change determination step S30 is repeatedly executed until the determination is Yes in the inspection completion determination step S28.

[0139] On the other hand, if it is determined that the print data will be changed in the print data change determination step S30, the determination is Yes. If the determination is Yes, the process proceeds to the print data acquisition step S10, where the print data is acquired, and the steps from the scanned image data acquisition step S12 to the print data change determination step S30 are repeatedly executed until the determination is Yes in the inspection completion determination step S28.

[0140] In the inspection end determination step S28, if it is determined that the end conditions for the defect inspection of the printed image are satisfied, the result is Yes. If the result is Yes, a specified end process is executed and the inspection method is ended.

[0141] [Operational Effects of the Embodiment] The image processing apparatus and inspection method according to the embodiment can achieve the following operational effects.

[0142] [1] The pixel values ​​of the print data are converted using pixel value information from the scanned image data, and reference image data used for inspecting the printed image is dynamically created each time scanned image data is acquired. This makes it possible to convert the print data into reference image data without depending on differences in printing conditions such as the print medium and ink, or the scanner's imaging conditions, thereby improving the accuracy of inspecting the printed image.

[0143] [2] When converting print data into reference image data, a lookup table is created for each color to be applied to the print data. This allows for high-speed conversion of print data into reference image data without performing complex calculations.

[0144] [3] A print pixel value map PM representing pixel values ​​for each pixel position in the print data and a scan pixel value map SM representing pixel values ​​for each pixel position in the scan image data for each color are created. This makes it possible to create a pixel value correspondence set SE, which is a set of pixel values ​​in the scan image data for each pixel value in the print data, based on the correspondence relationship between pixel values ​​at the same position in the print pixel value map PM and the scan pixel value map SM.

[0145] [4] The statistical value of a set of pixel values ​​in the scanned image data is calculated by using the arithmetic mean or median. This allows for a relatively short process, such as calculating the arithmetic mean, to calculate a more reliable statistical value.

[0146] [5] When print data containing multiple color information is acquired, pixel values ​​of the print data for each color are associated with pixel values ​​of the scanned image data for the same color as the print data, allowing for relatively simple processing for each color to be applied compared to relatively complex processing that takes into account correlation between colors.

[0147] [6] When print data containing multiple color information is acquired, the pixel values ​​of the print data contain information on multiple colors, which allows processing to take into account the influence of colors other than the color of interest.

[0148] [Example of application to a printing system] Fig. 17 is a block diagram showing an example of the configuration of a printing system including the image processing device shown in Fig. 1. The printing system 100 shown in Fig. 17 includes a medium supply device 102. The medium supply device 102 supplies the printing medium to a conveying device that conveys the printing medium in the printing system 100.

[0149] Note that a conveying device that conveys the print medium is not shown in Figure 17. The conveying device is indicated by the reference numeral 120 and is shown in Figure 18. The conveying device supports the print medium and conveys the print medium from the medium supply device 102 toward the medium collection device 112. The direction of the arrows shown in Figure 17 indicates the conveying direction of the print medium supported by the conveying device. The conveying direction of the print medium may be referred to as the medium conveying direction, the conveying direction, or the like.

[0150] The printing system 100 includes a pre-processing device 104. The pre-processing device 104 is disposed at a position downstream of the medium supplying device 102 in the medium transport direction. The downstream side in the medium transport direction refers to the side of the medium collecting device 112 in the medium transport direction.

[0151] The pretreatment device 104 performs a predetermined pretreatment on the print medium before printing, which is transported using the transport device. Examples of pretreatment performed using the pretreatment device 104 include temperature adjustment processing on the print medium, application of a pretreatment liquid to the print medium, and modification processing on the print medium. If pretreatment is not performed on the print medium before printing, the pretreatment device 104 may be omitted.

[0152] The printing system 100 includes a printing device 106. The printing device 106 prints on a print medium transported by a transport device based on specified print data. The printing device 106 may employ an inkjet system equipped with inkjet heads corresponding to multiple colors.

[0153] The inkjet head may be a line-type head in which a plurality of nozzles are arranged across a length corresponding to the entire width of the print medium in the medium width direction perpendicular to the medium transport direction. The line-type inkjet head may have a structure in which a plurality of head modules are arranged.

[0154] The inkjet head may be a serial type head that performs printing over the entire area of ​​the printing medium by moving the inkjet head and the printing medium relative to each other in the medium transport direction and the medium width direction.

[0155] The ejection method of the inkjet head may be a piezoelectric method that utilizes the flexural deformation of a piezoelectric element, a thermal method that utilizes the film boiling phenomenon of liquid, or an electrostatic method that utilizes the electric field formed between the inkjet head and the printing medium.

[0156] The printing method of the printing device 106 is not limited to the inkjet method. The printing device 106 may use an on-demand method such as electrophotography, or a plate-based printing method such as offset printing.

[0157] The printing system 100 includes a scanner 108. The scanner 108 is disposed at a position downstream of the printing device 106 in the media transport direction. The downstream side in the media transport direction refers to the side of the media collection device 112 in the media transport direction.

[0158] The scanner 108 reads the print image printed on the print medium and generates scan image data for each print image. The scan image data is sent to the inspection device 30. The printing system 100 may include a camera and a lighting device instead of the scanner 108.

[0159] The printing system 100 includes a post-processing device 110. The post-processing device 110 is disposed downstream of the scanner 108 in the medium transport direction. The post-processing device 110 performs post-processing on the print medium on which the print image has been printed. Examples of post-processing on the print medium include drying.

[0160] The positions of the scanner 108 and the post-processing device 110 may be interchanged. In the printing system 100 shown in Fig. 17, the print image is read using the scanner 108 before the print image is post-processed, but the print image may be read using the scanner 108 after the print image is post-processed.

[0161] The printing system 100 includes an image processing device 10 and an inspection device 30. The image processing device 10 creates reference image data to be applied to the inspection device 30 based on print data transferred from a printing device 106 and scanned image data transferred from a scanner 108.

[0162] The inspection device 30 is disposed at a position downstream of the post-processing device 110 in the medium transport direction. The inspection device 30 compares reference image data created in the image processing device 10 with scanned image data transferred from the scanner 108, and performs a defect inspection of the printed image on which the scanned image data is based. The inspection device 30 may transmit the results of the defect inspection of the printed image to the control device of the printing system 100.

[0163] The printing system 100 includes a medium collection device 112. The medium collection device 112 collects printed images printed based on print data. The medium collection device 112 may collect printed images that have passed inspection, where the inspection device 30 has obtained an inspection result indicating that no defects exist, and printed images that have failed inspection, where the inspection device 30 has obtained an inspection result indicating that defects exist.

[0164] [Electrical Configuration of Printing System] Figure 18 is a functional block diagram showing the electrical configuration of the printing system shown in Figure 17. The printing system 100 includes a control device 101 to which a computer is applied, and the control device 101 executes various programs corresponding to various functions to realize the various functions. The computer applied to the control device 101 may be a personal computer or the like, similar to the image processing device 10 shown in Figure 1.

[0165] The control device 101 is configured using one or more computers. In the control device 101, each of the various control units may be configured by one computer, or by multiple computers, or by one computer configuring multiple control units.

[0166] The control device 101 includes a system control unit 140. The system control unit 140 comprehensively controls the entire printing system 100. That is, the system control unit 140 transmits command signals to various processing units and controls each unit of the printing system 100 via the various processing units.

[0167] The control device 101 includes a transport control unit 142. The transport control unit 142 sets transport conditions for the print medium based on command signals sent from the system control unit 140 and controls the operation of the transport device 120. The transport device 120 shown in Fig. 18 supports the print medium and transports the print medium along a print medium transport path defined in the printing system 100.

[0168] The transport device 120 transports the medium between various devices that make up the printing system 100, such as the printing device 106. The transport device 120 also transports the medium between various devices that make up the printing system 100.

[0169] The printing system 100 includes a preprocessing control unit 144. The preprocessing control unit 144 sets preprocessing conditions for the preprocessing device 104 based on a command signal sent from the system control unit 140, and controls the operation of the preprocessing device 104.

[0170] The printing system 100 includes a print control unit 146. The print control unit 146 sets printing conditions and controls the operation of the printing device 106 based on command signals sent from the system control unit 140. The print control unit 146 includes a print data processing unit that generates halftone images for each color from the print data. The print control unit 146 also includes a control signal generation unit that generates control signals for the inkjet heads for each color based on the halftone images for each color.

[0171] The printing system 100 includes a scanner control unit 148. The scanner control unit 148 sets reading conditions for the scanner 108 and controls the operation of the scanner 108 based on a command signal transmitted from the system control unit 140. The scanner control unit 148 also acquires a read signal from the scanner 108. For example, the scanner control unit 148 acquires scanned image data from the scanner 108 as a read signal for a print image.

[0172] The printing system 100 includes a post-processing control unit 150. The post-processing control unit 150 sets post-processing conditions for the post-processing device 110 based on command signals sent from the system control unit 140, and controls the operation of the post-processing device 110.

[0173] The printing system 100 includes an inspection control unit 152. The inspection control unit 152 sets inspection conditions for the inspection device 30 based on command signals sent from the system control unit 140, and controls the operation of the inspection device 30.

[0174] The printing system 100 includes a print data acquisition unit 160 and a print condition acquisition unit 162. The print data acquisition unit 160 acquires print data that serves as the base data for printing. The print data may be called manuscript data, original image data, or the like.

[0175] The printing condition acquisition unit 162 acquires printing conditions to be applied to the printing device 106. Examples of printing conditions may include print resolution, print speed, type of printing medium, type of ink, etc. The printing control unit 146 applies the printing conditions acquired using the printing condition acquisition unit 162 to control the printing device 106.

[0176] [Example of Application to Lookup Table Manufacturing Method] The inspection method procedure shown in Fig. 16 includes a manufacturing method of a lookup table that functions as conversion data for converting pixel values ​​of print data according to the tendency of pixel values ​​of read data. That is, each of the steps from print data acquisition step S10 to pixel value conversion lookup table creation step S20 shown in Fig. 16 is applied to the manufacturing method of a lookup table.

[0177] [Example of application to a reference image data production method] The steps from print data acquisition step S10 to pixel value conversion step S22 in the inspection method procedure shown in Fig. 16 can be understood as a reference image data production method for creating reference image data to be used in inspecting printed matter. In other words, the image processing device 10 shown in Fig. 1 functions as a reference image data production device that produces reference image data to be sent to the inspection device 30.

[0178] The above-described embodiments of the present invention may be modified, added, or deleted as appropriate within the scope of the spirit of the present invention. The present invention is not limited to the above-described embodiments, and many modifications may be made by a person skilled in the art within the technical concept of the present invention. Furthermore, the embodiments, modifications, and applications may be implemented in appropriate combinations.

[0179] REFERENCE SIGNS LIST 10 Image processing device 12 Print data acquisition unit 14 Scanned image data acquisition unit 16 Pixel value map creation unit 18 Pixel value correspondence set creation unit 20 Statistical value calculation unit 22 Pixel value conversion lookup table creation unit 24 Pixel value conversion unit 30 Inspection device 32 Reference image data acquisition unit 34 Inspection target image data acquisition unit 36 ​​Comparison unit 38 Defect extraction unit 52 Processor 54 Computer readable medium 56 Communication interface 58 Input / output interface 60 Bus 62 Memory 64 Storage 66 Input device 68 Display 70 Print data acquisition program 72 Scanned image data acquisition program 74 Pixel value map creation program 76 Pixel value correspondence set creation program 78 Statistical value calculation program 80 Pixel value conversion lookup table creation program 82 Pixel value conversion program 100 Printing system 101 Control device 102 Medium conveying device 104 Pre-processing device 106 Printing device 108 Scanner 110 Post-processing device 112 Medium collection device 140 System control unit 142 Transport control unit 144 Pre-processing control unit 146 Printing control unit 148 Scanner control unit 150 Post-processing control unit 152 Inspection control unit 160 Print data acquisition unit 162 Printing condition acquisition unit S10 to S30 Steps of inspection method LutR Lookup table LutG Lookup table LutB Lookup table PM Print pixel value map P 11 Pixel position P 12 Pixel position P 13 Pixel position P 21 Pixel position P 22 Pixel position P 23 Pixel position RI Reference image data SE Pixel value correspondence set SM Scan pixel value map SV Statistical value

Claims

1. An image processing method comprising the steps of: acquiring first image data; acquiring second image data generated by reading a first image from which the first image data is output; creating conversion data for converting the first pixel values ​​in the first image data for each color based on a statistical value of a set of second pixel values ​​for each of the first pixel values, the second pixel values ​​representing pixel values ​​for each pixel position in the second image data and corresponding to first pixel values ​​representing pixel values ​​at the same pixel position in the first image data; and converting the first pixel values ​​of the first image data for each color using the conversion data created each time the second image data is acquired.

2. The image processing method of claim 1, further comprising the steps of: creating a first pixel value map representing the first pixel value for each pixel position of the first image data; creating a second pixel value map representing the second pixel value for each pixel position of the second image data; and using the first pixel value map and the second pixel value map to associate the second pixel value with the first pixel value at the same pixel position in the first image data.

3. The image processing method according to claim 1, wherein the statistical value is an arithmetic mean value or a median value.

4. The image processing method of claim 1, further comprising the steps of: acquiring the first image data containing information on a plurality of colors; and associating the second pixel value for each pixel position in the second image data for each color with the first pixel value of the same pixel position in the first image data of the same color as the second image data.

5. The image processing method according to claim 1, further comprising the steps of: acquiring the first image data containing information on a plurality of colors; and associating the second pixel value for each pixel position in the second image data for each color with the first pixel value of the first image data containing information on a plurality of colors.

6. The image processing method according to claim 1, further comprising the steps of: creating a lookup table as the conversion data for converting the first pixel values ​​of the first image data for each color; and using the lookup table to convert the first pixel values ​​of the first image data, thereby creating reference data for use in inspecting defects in an output image of the first image data.

7. The image processing method according to claim 1, further comprising the steps of: acquiring print data serving as a manuscript for printing as the first image data; and acquiring read data for each color of a print image printed by applying the print data as the second image data.

8. An image processing device comprising: one or more processors; and one or more memories storing a program including one or more instructions executed by the one or more processors, wherein the one or more processors execute the program to acquire first image data; acquire second image data generated by reading a first image from which the first image data is output; create conversion data for converting the first pixel value in the first image data for each color based on a statistical value of a set of second pixel values ​​for each first pixel value, the second pixel value representing a pixel value for each pixel position in the second image data and corresponding to a first pixel value representing a pixel value at the same pixel position in the first image data; and convert the first pixel value of the first image data for each color using the conversion data created each time the second image data is acquired.

9. A program for enabling a computer having one or more processors and one or more memories storing a program including one or more instructions executed by the one or more processors to realize the following functions: acquiring first image data; acquiring second image data generated by reading a first image to which the first image data is output; creating conversion data for converting the first pixel value in the first image data for each color based on a statistical value of a set of second pixel values ​​for each first pixel value, the second pixel value representing a pixel value for each pixel position in the second image data and corresponding to a first pixel value representing a pixel value at the same pixel position in the first image data; and converting the first pixel value of the first image data for each color using the conversion data created each time the second image data is acquired.

10. A non-transitory computer-readable recording medium having the program according to claim 9 recorded thereon.

11. Conversion data, which converts the first pixel value in the first image data for each color based on a statistical value of the set of second pixel values ​​for each first pixel value, for second pixel values ​​corresponding to first pixel values ​​representing pixel values ​​at the same pixel position in the first image data, the second pixel values ​​representing pixel values ​​for each pixel position in the first image data.

Images