JP2015221514A - Image forming apparatus, image forming method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image forming apparatus capable of improving analysis efficiency in a system for analyzing a printed matter.SOLUTION: Information on frequency components showing the degree of variation of pixel value is obtained by analyzing data to be printed. A region to be inspected to detect printing defect is specified on the data to be printed on the basis of the obtained information on the frequency components. A matter to be printed is printed on the basis of the data to be printed, and reading data is generated by reading the printed matter. In the specified region, the data to be printed and the reading data are compared, and the printing defect in the printed matter is detected on the basis of the comparison result.

Description

  The present invention relates to an image forming apparatus, an image forming method, and a program for performing analysis processing on a printed matter.

  In recent years, inkjet printers have been increasingly used for commercial printing applications such as photographs due to the development of inkjet recording technology. Under such circumstances, inkjet printers for commercial printing applications are increasingly required to have high speed and high image quality. In response to the demand for higher speed, inkjet printers equipped with line-type recording heads have become common.

  For example, ink jet recording color printers are roughly classified into two types based on the difference in printing operation of the recording head with respect to the recording paper during printing. One is a type in which the recording head reciprocates in the main scanning direction and the recording paper is conveyed in the sub scanning direction, and is called a serial type printer. Furthermore, one is a type in which a line-type recording head having a length substantially the same as the width of the recording paper is fixed to the apparatus, and only the recording paper is conveyed along the sub-scanning direction with respect to the line-type recording head. It is called a line type printer.

  However, compared with a serial type printer, an ink jet printer with a line type recording head has a drawback that an image defect due to the characteristics of the recording head is likely to be visually recognized. This is because the recording paper passes through the recording head only once, so that the recording head characteristics appear on the image as it is. Here, the defect on the image due to the recording head characteristics refers to a phenomenon in which, for example, a white streak is generated without ejecting an ink droplet from a nozzle.

  In order to solve such a problem, a configuration for performing a defect inspection of a printed image is known. Patent Document 1 describes that a periodic defect appearing on an image is detected by reading a printed matter with a reading device such as a scanner and performing frequency analysis. Japanese Patent Application Laid-Open No. H10-228561 describes that the first printed matter is read by an input device such as a CCD camera, and the read image data is compared with the printed image data. Then, it is described that a defect on the paper surface such as a white stripe due to nozzle non-discharge on the image is detected based on information such as a density difference.

Japanese Patent Laid-Open No. 2005-043769 JP 2006-334835 A

  However, in the configuration described in Patent Document 1, since the entire printed area is read and frequency analysis is performed on the entire read area, the analysis processing load is large. Further, as the speed of the printer increases, the defect inspection system also needs to be speeded up. However, since the frequency analysis process is a process with a large processing load, it is not easy to increase the speed. Further, since reading is performed on the entire printed area, the memory capacity for temporarily storing the read image is increased. Also in Patent Document 2, since the entire area of the print image is read and the entire area is compared with the print image data, the processing load is large.

  An object of the present invention is to solve such conventional problems. In view of the above points, an object of the present invention is to provide an image forming apparatus, an image forming method, and a program that improve the efficiency of analysis in a system for analyzing printed matter.

  In order to solve the above-described problems, an image forming apparatus according to the present invention is an image forming apparatus capable of detecting a print defect based on a printing result on a printed material, and analyzes data to be printed, and the data to be printed Acquisition means for acquiring frequency component information representing the degree of change in pixel value as a feature quantity, and detection of the print defect on the print target data based on the frequency component information acquired by the acquisition means A specifying unit that specifies a target area; a printing unit that prints a printed material based on the data to be printed; a reading unit that reads the printed material printed by the printing unit and generates read data; and the specifying unit A comparison unit that compares the data to be printed with the read data read by the reading unit in the region specified by Based on the results of the comparison, characterized in that it comprises a detecting means for detecting printing defects in the printed material printed by said printing means.

  ADVANTAGE OF THE INVENTION According to this invention, the efficiency of analysis can be improved in the system for analyzing printed matter.

1 is a block diagram illustrating a configuration of an image forming apparatus. It is a figure which shows the functional block of an image forming apparatus. It is a flowchart which shows the procedure of the process which performs a printing defect inspection. It is a schematic diagram which shows the result of having performed frequency analysis with respect to image data. It is a figure which shows a response | compatibility with a frequency domain and human contrast sensitivity. 6 is a flowchart illustrating a procedure of print data generation processing. It is a figure which shows the relationship between the number of recording dots, density | concentration, and a frequency. It is a flowchart which shows the procedure of the other process which performs a printing defect inspection. It is a figure which shows a MacAdam ellipse. It is a flowchart which shows the procedure of the other process which performs a printing defect inspection. It is a figure which shows the correspondence of CMYK and L * a * b * information.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments do not limit the present invention according to the claims, and all combinations of features described in the embodiments are not necessarily essential to the solution means of the present invention. . The same constituent elements are denoted by the same reference numerals, and the description thereof is omitted.

  FIG. 1 is a block diagram illustrating a configuration of an image forming apparatus according to the present embodiment. An image forming apparatus 100 illustrated in FIG. 1 is a so-called MFP (Multi Functional Preference) in which a plurality of functions such as a printing function, a scanning function, and a FAX function are integrated. In the present embodiment, the image forming apparatus 100 is an image forming apparatus capable of detecting a print defect from a printing result on a printed material. The detection of printing defects will be described later.

  The main body of the image forming apparatus 100 includes a CPU 101, a ROM 102, a RAM 103, a video card 104, a storage device 105, a network interface card (NIC) 106, and an interface 107. They are connected to each other by a system bus 115. The CPU 101 controls each unit of the image forming apparatus 100, and reads out a program stored in the ROM 102 or the storage device 105 to the RAM 103 and executes it, thereby realizing the operation of the present embodiment described later. The RAM 103 is also used as a working memory for the CPU 101. The video card 104 connects a monitor 108 as a display unit to the main body of the image forming apparatus 100. The monitor 108 is a touch panel, for example. The storage device 105 is, for example, a hard disk drive (HDD) or a memory card.

  The NIC 106 connects the image forming apparatus 100 to a network 109 such as a LAN, and enables mutual communication with other apparatuses on the network 109. The interface 107 connects various devices to the main body of the image forming apparatus 100. The interface 107 is a serial bus interface such as USB or IEEE1394. In FIG. 1, a printer 110 (printing unit), a CCD camera 111 and a scanner 112 (reading unit), a keyboard 113, and a pointing device 114 are connected via an interface 107. The image forming apparatus 100 may include other blocks not shown in FIG. In addition, the monitor 108 and the printer 110 to the pointing device 114 may be configured in the main body of the image forming apparatus 100.

  FIG. 2 is a diagram illustrating functional blocks according to the present embodiment of the image forming apparatus 100. The image forming apparatus 100 includes an image input unit 201, an input image analysis unit 202, a defect inspection condition setting unit 203, a print data generation unit 204, a printing unit 205, a printed material reading unit 206, and a printed material inspection unit 207. The image input unit 201 inputs defect inspection target image data to the image forming apparatus 100. For example, the image input unit 201 inputs image data from a device that optically acquires image data, such as a digital camera or digital video. The image input unit 201 may input image data from a portable medium such as a magnetic disk, an optical disk, or a memory card. Note that the image data input by the image input unit 201 may be input in the form of an image file.

  The input image analysis unit 202 performs frequency analysis on the image data input by the image input unit 201. As will be described later, in the present embodiment, the defect inspection is performed only on a region that is identified as a human image defect that is easily recognized as an image defect in the input image data as a result of the frequency analysis. The input image analysis unit 202 calculates an average value of frequency components for each region of about 1 mm that is easy for humans to visually recognize (that is, a plurality of pixel group units). Then, the input image analysis unit 202 stores the calculated average value of the frequency components in a storage area such as the RAM 103 as a frequency analysis result.

  The defect inspection condition setting unit 203 sets conditions for specifying an inspection target region for performing defect inspection based on the frequency analysis result obtained by the input image analysis unit 202. Here, the set condition is a value (threshold value) related to a frequency component that serves as a reference for specifying the inspection target region. In the present embodiment, the input image analysis unit 202 performs frequency analysis on the image data. For example, the frequency analysis analyzes the degree of change in the main scanning direction and the sub-scanning direction for the pixel value of the image data. The The change in pixel value represents a change in color, for example. For example, a blue sky photographic image has a smaller color change than a dot image. In the present embodiment, as a result of the image data being analyzed by the input image analysis unit 202, an image region having a frequency component (low frequency component) equal to or lower than a threshold is specified as an inspection target region for defect inspection.

  In the present embodiment, the inspection target area specified by the defect inspection condition setting unit 203 is an area containing a lot of low frequency components. Here, the reason why the region including a lot of low frequency components is specified as the inspection target region will be described. In general, from the viewpoint of human visual characteristics, the lower the frequency component of an image, the easier it is to recognize a color difference or the like, while the higher the frequency, the less difficult it is to recognize. The defect of the printed matter assumed in the present embodiment refers to, for example, white stripes due to non-ejection of ink from the nozzles of the recording head, and color unevenness due to different nozzle characteristics in the recording head. The defect of such printed matter is caused by the occurrence of an unexpected color difference with the surroundings, and the color difference is more easily recognized as a defect as the frequency component is lower. In the present embodiment, the load of defect inspection processing is reduced by specifying an area that is easily recognized as a defect by a person as an inspection target area.

  The print data generation unit 204 generates print data based on the image data input by the image input unit 201. The format of the image data input by the image input unit 201 is, for example, sRGB, and the print data generation unit 204 converts the format of the image data into a format that can be printed by the printer 110. Based on the print data generated by the print data generation unit 204, the printing unit 205 prints on a recording medium such as a print sheet by the printer 110. The printed material reading unit 205 optically reads an image on the printed material printed by the printing unit 205 using the scanner 112. Here, the CCD camera 111 and the scanner 112 are used as devices for reading, but other devices may be used as long as they are devices that can optically read printed matter.

  The printed matter inspection unit 207 performs defect inspection on the inspection target region of the read data read by the printed matter reading unit 206. In the present embodiment, a configuration for inspecting printing defects such as white streaks due to non-ejection of ink from the nozzles of the recording head and color unevenness due to nozzle characteristics will be mainly described. However, with respect to various other types of printing defects, the load of defect inspection processing can be reduced according to the present embodiment.

  Hereinafter, a case where the image forming apparatus 100 is an ink jet recording apparatus that performs printing with four color inks of C (cyan), M (magenta), Y (yellow), and K (black) will be described. However, the image forming apparatus 100 may include ink of other colors such as light cyan, light magenta, red, and green. In the present embodiment, a case will be described in which the image data input by the image input unit 201 is image data defined in the sRGB color space. However, it may be image data defined in other color spaces such as CMYK and extended colors.

  FIG. 3 is a flowchart showing a procedure of processing for performing a print defect inspection in the present embodiment. Each process shown in FIG. 3 is realized, for example, when the CPU 101 reads a program from the ROM 102 into the RAM 103 and executes it. First, in step S <b> 301, the CPU 101 inputs image data to be printed by the image input unit 201. For example, the CPU 101 inputs image data via the interface 107 and stores it in the storage device 105. The image data input in the present embodiment is assumed to have a resolution of 300 dpi, for example.

  In step S <b> 302, the CPU 101 sets conditions for performing frequency analysis using the defect inspection condition setting unit 203. Here, the set conditions are, for example, the size of a unit region when performing frequency analysis and a threshold value for specifying a low frequency region. In the present embodiment, for example, for a 300 dpi image data, a unit area of 100 pixels square having a size of about 1 cm square is set. Note that the setting condition may be a fixed value or a variable value corresponding to the size or resolution of the image data. In addition, conditions set by the operator via the pointing device 114 or the keyboard 113 may be accepted.

  In step S303, the CPU 101 causes the input image analysis unit 202 to perform frequency analysis on the image data input in step S301 based on the conditions set in step S302. Here, a frequency analysis method defined by a general method may be used. The CPU 101 calculates an average value of frequency components for each unit region set in S302 as a feature amount of image data.

  FIG. 4 is a schematic diagram illustrating a result of frequency analysis performed on input image data. FIG. 4A shows the input image data, and FIG. 4B shows the result of frequency analysis performed on the image data of FIG. An object 401 represents a plant, an object 402 represents a person, an object 403 represents a building, and an object 404 represents a cloud floating in the blue sky. A region 405 in FIG. 4B represents a region of a frequency component lower than the threshold set in S302 as a result of frequency analysis. As a result of the frequency analysis, an area where a change in RGB value (an example of a pixel value) for each pixel is small, such as a blue sky, is specified as a low frequency area. In this way, by performing frequency analysis on the input image data, a region containing objects such as buildings, plants, and people is used as a high-frequency component region, and a region in which the same color such as a blue sky is distributed is a low-frequency component. Can be separated as regions.

  FIG. 5 is a diagram illustrating the correspondence between the frequency domain and human contrast sensitivity. The horizontal axis in FIG. 5 represents spatial frequency, and the vertical axis represents human contrast sensitivity. The correspondence shown in FIG. 5 is known as visual spatial frequency characteristics (MTF) represented by Dooley and Barten. The higher the contrast sensitivity, the easier it is for humans to perceive differences in brightness (color). That is, as shown in FIG. 5, human visual characteristics have high contrast sensitivity in the low frequency to intermediate frequency range (a color difference is easily detected), and low contrast sensitivity in the high frequency range (color Difficult to perceive the difference).

  In the present embodiment, a threshold value for distinguishing the low frequency region 501 and the high frequency region 502 is set, and the low frequency region 501 with high human contrast sensitivity is specified as a print defect inspection target region. Further, the inspection target area may be adjusted by changing the threshold value.

  Reference is again made to FIG. In S304, the CPU 101 specifies the inspection target area based on the result analyzed in S303. In specifying the region to be inspected, a region that is specified as containing a lot of low-frequency components below the threshold is selected from the analysis result of S303. The selected result is, for example, a region 405 in FIG. Depending on the printer 110, there may be a scaling process for enlarging / reducing an input image depending on the size of the printing paper, or an allocation process for allocating and printing a plurality of images on one printing paper. Even in such a case, by associating the print data and the image data based on the scaling setting or the assignment setting, it is possible to appropriately specify the inspection target region on the read data described later.

  In step S <b> 305, the CPU 101 causes the print data generation unit 204 to generate print data based on the image data. For example, print data defined in a color space corresponding to the printer is generated by performing color space conversion on image data defined in the sRGB color space.

  FIG. 6 is a flowchart illustrating a procedure of print data generation processing in step S305. In step S <b> 601, the CPU 101 converts an RGB original image signal acquired by an image input device such as a digital camera or a scanner or computer processing into an R′G′B ′ signal by color processing A. Here, the color processing A is processing for converting the original image signal RGB into an image signal R′G′B ′ adapted to the color reproduction range of the printer. In step S <b> 602, the CPU 101 converts the R′G′B ′ signal into a signal corresponding to each color ink by the color processing unit B. For example, since the ink colors used in the image forming apparatus 100 are four colors, the converted signals are density signals C1, M1, Y1, and K1 corresponding to cyan, magenta, yellow, and black. In color processing B, a three-dimensional lookup table (3DLUT) of RGB input and CMYK output is used, and for input values outside the grid points, output values are calculated by interpolation from the output values of the surrounding grid points. .

  In step S603, the CPU 101 performs gamma correction on the density signals C1, M1, Y1, and K1 by gamma correction using the correction table, and acquires C2, M2, Y2, and K2. In step S604, the CPU 101 binarizes the density signals C2, M2, Y2, and K2 after the gamma correction by quantization, and further converts them into image signals C3, M3, Y3, and K3 to be transferred to the recording head. An error diffusion method, a dither method, or the like is used as a quantization (binarization) method. For example, in the dither method, binarization is performed using a predetermined dither pattern having a different threshold for the density signal of each pixel.

  Please refer to FIG. 3 again. In step S306, the CPU 101 causes the printing unit 205 to perform printing based on the print data generated in step S305. In S306, for example, a printing method of an ink jet printer using a piezoelectric element or foaming energy is used. In step S <b> 307, the CPU 101 causes the printed material reading unit 206 to read the printed material printed in step S <b> 306 and generates read data. The read data is temporarily stored in the RAM 103. For example, a scanner 112 or a CCD camera 111 is used as a device for optically reading an image when reading a printed matter.

  In step S308, the CPU 101 performs a print defect inspection on the inspection target area specified in step S304 of the read data generated in step S307. Here, an example of a print defect inspection will be described. First, based on the print data generated in S305, the CPU 101 generates predicted image data in which a printed material reading result is predicted. A reading device such as the scanner 112 has solid characteristics due to tolerances in manufacturing a light source, a sensor, and the like. In the present embodiment, the individual difference of the reading device is acquired, and predicted image data reflecting the individual difference is generated. Next, the CPU 101 compares the read data generated in S307 with the predicted image data, and calculates the difference. The CPU 101 determines whether a print defect has occurred in the printed matter from the difference calculation result.

  In the present embodiment, predicted image data is generated for the inspection target area specified in S304 and compared with the read data. It should be noted that the determination criteria for defect inspection may be adjustable by changing the condition of the difference value for determining that a print defect has occurred.

  In step S309, the CPU 101 determines whether a print defect has been detected in step S308. If it is determined that no print defect has been detected, the process of FIG. 3 is terminated. If it is determined that a print defect has been detected, the process proceeds to S310. In step S310, the CPU 101 performs reprinting on the print data corresponding to the read data determined to have detected a print defect. Regarding reprinting at the time of detecting a print defect, for example, the print data generated in S305 may be stored in a storage area such as the RAM 103 so that it is automatically reprinted when a print defect is detected. Alternatively, reprinting may be performed after receiving a reprinting instruction from an operator (user). Further, the read data in which the print defect is detected may be displayed on the monitor 108 so that the operator can confirm, and the reprint may be performed after receiving the reprint instruction from the operator.

  As described above, in this embodiment, based on the frequency analysis result of the input image data, the inspection target area to be subjected to the print defect inspection is specified as a part to reduce the inspection processing load. As a result, it is possible to efficiently inspect a region that is easily identified as a print defect when a human sees the print, and to perform a print defect inspection of the print with high speed and accuracy.

  In the above description, the frequency analysis is performed on the input image data. However, the frequency analysis may be performed on the read data. Further, although the operation of specifying the inspection target area by reading the entire area of the printed material has been described, the reading area may be limited to the inspection target area at the time of reading. With such a configuration, it is possible to reduce loads such as reading processing and reading data transfer processing, and it is possible to reduce memory in a storage area in which reading data is temporarily stored.

  In the present embodiment, JPEG, which is an international standard system for compressing and encoding still images, is used as the format of input image data. However, other formats such as bmp and tiff may be used. When JPEG is used, frequency analysis may be performed based on frequency information described in JPEG data.

  Further, although the configuration in which print defect detection is performed only in the low frequency region has been described, simple print defect detection may be further performed in the high frequency region. For example, a simple print defect detection may be performed separately for the high frequency region by configuring to detect a plurality of types of print defects with different algorithms. Or it is good also as a structure which detects a printing defect simply with respect to a high frequency area | region by changing the conditions of resolution and a threshold value.

[Second Embodiment]
In the present embodiment, a configuration for performing frequency analysis on print data and specifying an inspection target region will be described. In the first embodiment, it has been described that frequency analysis is performed on input image data to reduce the processing load of print defect detection. The human visual characteristic with respect to the frequency change of FIG. 5 can be similarly applied to the number of dots printed on the paper surface. Hereinafter, a configuration for specifying an inspection target region by performing frequency analysis on dot data (print data) to be ejected from the nozzles of the recording head will be described.

  In an ink jet recording type printer, printing is performed by ejecting ink droplets from a recording head. At that time, in the highlight area of low density, the color is expressed by a small number of recording dots, and in the dark area of high density, the color is expressed by a large number of recording dots.

  FIG. 7A is a diagram showing the relationship between the number of recording dots and the density, and FIG. 7B is a diagram showing the relationship between the number of recording dots and the frequency. As shown in FIG. 7A, when the number of recording dots is small, the change in density is steep, but when the recording surface is completely filled with recording dots, the change in density becomes small and a gentle curve is obtained. Further, as shown in FIG. 7B, the frequency increases as the number of recording dots increases until the number of recording dots fills the paper surface. The frequency decreases. That is, by covering the paper surface with recording dots, the paper surface is covered with a single color, and the frequency is lowered to a low frequency region. In the present embodiment, the detection target region is specified by paying attention to the frequency component of the recording dots of the ink jet recording method that performs such gradation expression. Hereinafter, differences from the first embodiment will be described.

  FIG. 8 is a flowchart showing a procedure of processing for further specifying the inspection target region by performing frequency analysis on the print data after specifying the low frequency region for the image data. S801 is the same as the description in S301 of FIG.

  In step S <b> 802, the CPU 101 sets conditions for performing frequency analysis using the defect inspection condition setting unit 203. Here, the set conditions include, for example, the size of the unit area when performing frequency analysis, the first threshold value for specifying the low frequency area for the image data, and the low frequency for the print data. This is a second threshold value for specifying the region. The first threshold corresponds to the threshold described in S302.

  The print data may be subjected to a scaling process such as enlargement / reduction depending on the size of the printing paper. Here, it is assumed that printing is performed at a recording dot resolution of 600 dpi, and analysis is performed for each unit area of 200 pixels that is about 1 cm square. The recording dot resolution of the printer is an index indicating how accurately the recording dots can be printed on the printing paper, and is a characteristic unique to the apparatus. The setting condition such as the size of the unit area may be a fixed value or a variable value corresponding to the recording dot resolution.

  S803 to 805 are the same as those described in S303 to S305 of FIG. Here, the inspection target area specified in S804 is set as a first inspection target area.

  In step S806, the CPU 101 performs frequency analysis on the print data generated in step S805 based on the conditions set in step S802. Here, frequency analysis determined by a general method is performed on the dot data ejected on the paper. The CPU 101 calculates an average value of frequency components for each unit area set in S802 as a feature amount of the print data.

  In step S <b> 807, the CPU 101 specifies an inspection target area (second inspection target area) based on the result analyzed in step S <b> 806. In specifying the region to be inspected, a region that is specified as containing a lot of low-frequency components equal to or lower than the second threshold value is selected from the analysis result of S806. In step S808, an inspection target region in which the print defect inspection in the present embodiment is performed on the region corresponding to both the first inspection target region specified in step S804 and the second inspection target region specified in step S807 ( The third inspection target area) is specified. S809 to S813 are the same as those described in S306 to 310 of FIG.

  As described above, in the present embodiment, the frequency analysis is performed on the dot data ejected on the paper surface, thereby further specifying the inspection target area for performing the print defect inspection, and further reducing the processing load of the print defect inspection. can do. In this embodiment, the frequency analysis is performed on the input image data. However, the configuration may be such that only the print data is the target of the frequency analysis.

[Third Embodiment]
In the present embodiment, a configuration for specifying a region to be inspected using information on color and saturation after printing will be described. In the first embodiment, frequency analysis is performed on input image data. In the second embodiment, frequency analysis is performed on dot data on the paper. The human visual characteristic with respect to the frequency change of FIG. 5 can be similarly applied to color and saturation. In the present embodiment, a configuration for specifying a region to be inspected based on color information at the time of printing will be described.

  Here, color and human visual characteristics will be described. In general, color information is defined in various color space coordinate systems such as L * a * b * space and LCH space. In the present embodiment, it is assumed that the color information is expressed in L * a * b * space.

  FIG. 9 is a diagram showing a MacAdam ellipse. In FIG. 9, the horizontal axis represents the a * component, and the vertical axis represents the b * component. In the a * b * plane of FIG. 9, the ease of recognizing a human color difference is expressed. A plurality of small ellipses are illustrated in FIG. 9, which indicates that humans are insensitive to color differences within the ellipse. Humans have the property that the higher the saturation region, the less likely the color difference is noticed, and the difficulty of being noticed at that time is different depending on the hue. This embodiment uses the principle that areas that are more easily noticed in color differences are more likely to notice printed defects in printed matter, specify the inspection target area using color saturation information and hue information, and perform print defect inspection processing. The load is reduced. Hereinafter, differences from the first and second embodiments will be described.

  FIG. 10 is a flowchart illustrating a procedure of processing for performing color information prediction and specifying an inspection target region based on the prediction information. S1001 is the same as the description in S301 of FIG.

  In step S <b> 1002, the CPU 101 sets conditions for performing frequency analysis using the defect inspection condition setting unit 203. Here, the set conditions include, for example, the size of a unit area when performing frequency analysis, a threshold value for specifying a low frequency area for image data, and L * a * b for color prediction. * Information. The setting of L * a * b * information for color prediction is, for example, the setting of L * a * b * information corresponding to the elliptical area in FIG. Alternatively, since a print defect in an image such as a skin color area, for example, a human face is easily noticeable, L * a * b * information corresponding to the skin color area may be received by a designation operation by an operator. In this case, for example, settings such as “L *: 10 to 80, a *: 0 to 50, b *: 0 to 50” are accepted on the setting screen displayed on the monitor 108. Alternatively, a color patch such as skin color or sky blue may be prepared in advance and L * a * b * information corresponding to the color of the color patch selected by the user may be received.

  S1003 to S1005 are the same as those described in S303 to S305 of FIG. In step S1006, the CPU 101 performs color prediction during printing based on the print data generated in step S1005. In the present embodiment, color prediction is performed based on a database in which print data and L * a * b * information are associated with each other.

  FIG. 11 is a diagram illustrating an example of a database showing a correspondence relationship between CMYK print data and L * a * b * information. FIG. 11 shows L * a * b * values when the signal value of each CMYK is 100. In such a database, color prediction can be performed with higher accuracy by holding L * a * b * values in which the increments of signal values of each CMYK are set more finely.

  In step S1007, the CPU 101 identifies an area in which a color difference is likely to be recognized based on the color information predicted in step S1006 and the condition set in step S1002. In step S <b> 1008, the CPU 101 performs a print defect inspection in the present embodiment on an area corresponding to both the inspection target area specified in step S <b> 1004 and the area where the color difference specified in step S <b> 1007 is likely to be recognized. It is specified as the inspection target area. S1009 to S1013 are the same as those described in S306 to S310 of FIG.

  As described above, in the present embodiment, frequency analysis is performed on input image data, a color at the time of printing is predicted, and an inspection target region is specified in consideration of the color prediction information. . As a result, the processing load for printing defect inspection can be further reduced.

  In the present embodiment, the configuration for performing color prediction on the entire area of the print data has been described. However, color prediction may be performed only for the area determined as the low frequency area on the image data in S1004. With such a configuration, the load of color prediction processing can be reduced, and the load of calculation processing in the apparatus can be reduced.

  The present invention is also realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

  100 image forming apparatus, 101 CPU, 102 ROM, 103 RAM

Claims (10)

An image forming apparatus capable of detecting a printing defect based on a printing result on a printed material,
An acquisition unit that analyzes data to be printed and acquires frequency component information representing a degree of change in pixel value as a feature amount of the data to be printed;
Based on the information of the frequency component acquired by the acquisition unit, a specifying unit that specifies a region to be detected of the print defect on the print target data;
Printing means for printing a printed material based on the data to be printed;
Reading means for reading the printed matter printed by the printing means and generating read data;
Comparison means for comparing the data to be printed with the read data read by the reading means in the area specified by the specifying means;
Detecting means for detecting a print defect of the printed matter printed by the printing means based on a result of comparison by the comparing means;
An image forming apparatus comprising: The acquisition means analyzes each of the data before being converted into the color space for printing and the data after being changed into the color space for printing, and acquires frequency component information,
The specifying unit specifies a first region based on frequency component information acquired by the acquiring unit from data before being converted to the printing color space, and is converted into the printing color space. A second area is identified based on the frequency component information acquired by the acquisition means from the subsequent data, and the print defect detection target area is determined based on the first area and the second area. The image forming apparatus according to claim 1, wherein the image forming apparatus is specified.   The image forming apparatus according to claim 2, wherein the specifying unit specifies an area where the first area and the second area overlap as an area to be detected by the print defect. A second specifying means for specifying an area based on the specified color information;
4. The comparison unit according to claim 1, wherein the comparison unit compares the data to be printed with the read data in an area specified by the specifying unit and the second specifying unit. The image forming apparatus described in the item.   The said specifying means specifies the area | region of the frequency component below a threshold value on the said printing object data as an area | region of the said detection target of the printing defect, The any one of Claim 1 thru | or 4 characterized by the above-mentioned. Image forming apparatus.   6. The printing apparatus according to claim 1, wherein the printing unit performs printing by ejecting ink droplets onto a recording medium, and the printing defect is uneven color due to the ejected ink droplets. The image forming apparatus described. An image forming apparatus capable of detecting a printing defect based on a printing result on a printed material,
An acquisition unit that analyzes the data to be printed and acquires color information as a feature amount of the data to be printed;
Based on the color information acquired by the acquisition means, a specifying means for specifying a region to be detected for the print defect on the data to be printed;
Printing means for printing a printed material based on the data to be printed;
Reading means for reading the printed matter printed by the printing means and generating read data;
Comparison means for comparing the data to be printed with the read data read by the reading means in the area specified by the specifying means;
Detecting means for detecting a print defect of the printed matter printed by the printing means based on a result of comparison by the comparing means;
An image forming apparatus comprising: An image forming method executed in an image forming apparatus capable of detecting a print defect based on a printing result on a printed material,
An acquisition step of analyzing data to be printed and acquiring frequency component information representing a degree of change in pixel value as a feature amount of the data to be printed;
Based on the information of the frequency component acquired in the acquisition step, a specifying step of specifying the print defect detection target area on the print target data;
A printing process for printing a printed material based on the data to be printed;
A reading step of reading the printed matter printed in the printing step and generating read data;
A comparison step for comparing the data to be printed with the read data read in the reading step in the area specified in the specifying step;
A detection step of detecting a print defect of the printed matter printed in the printing step based on a result of the comparison in the comparison step;
An image forming method comprising: An image forming method executed in an image forming apparatus capable of detecting a print defect based on a printing result on a printed material,
An analysis step of analyzing the data to be printed and obtaining color information as a feature amount of the data to be printed;
Based on the color information acquired in the acquisition step, a specifying step of specifying a region to be detected for the print defect on the data to be printed;
A printing process for printing a printed material based on the data to be printed;
A reading step of reading the printed matter printed in the printing step and generating read data;
A comparison step for comparing the data to be printed with the read data read in the reading step in the area specified in the specifying step;
A detection step of detecting a print defect of the printed matter printed in the printing step based on a result of the comparison in the comparison step;
An image forming method comprising:   A program for causing an image forming apparatus to execute each step of the image forming method according to claim 8.

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