JP2016060191A - Image defect detection apparatus, image defect detection method, image-recording apparatus, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image defect detection apparatus, image defect detection method, image-recording apparatus, and program capable of setting an optimum condition for detecting an image defect according to a print source image and properly detecting the image defect.SOLUTION: The problem is solved by an image defect detection apparatus that comprises: image defect addition setting means for setting a position in a print source image at which an image defect is intentionally added; image feature quantity acquisition means for acquiring the image feature quantity of the position in the print source image at which the image defect is added; defect-added image generation means for generating a defect-added image, or an image to which the image defect was added, at the position set by the image defect addition setting means in the print source image; determination result acquisition means for acquiring the result of a determination made as to whether or not it is allowable that the image detect is present in the detect-added image printed by a print head; and detection condition setting means for setting an image defect detection condition from the image feature quantity of the position at which the image defect was added and the determination result.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an image defect detection apparatus and method, an image recording apparatus, and a program, and more particularly to an image processing technique for performing an image defect detection process under conditions according to a printed matter.

  The image defect detection process for determining whether the printed material is acceptable or not is performed according to detection conditions set in advance. Therefore, the number of sheets that are rejected and insufficient is determined in advance based on experience, and the number of sheets necessary for shipment is added to print. However, if the detection conditions are too strict, the number of rejected sheets will increase and the number of accepted sheets will be insufficient. Therefore, it is necessary to further increase the amount added to the required number of shipments. On the other hand, if the detection conditions are too loose, there is a problem in that productivity is reduced due to excessive printing.

  In order to solve such a problem, in Patent Document 1, when high-precision printing is required, a high-level pass / fail criterion is set for all areas, and a lightly defective portion can be detected for all areas. On the other hand, in the case of packaging boxes for confectionery, etc., the level of the quality standard of the surface on which the product name is printed is increased, and the area that is difficult to visually recognize from the outside by gluing when making a box body Techniques for lowering levels are described.

JP 2009-133741 A

  The detection conditions are determined based on the experiences of the printing company and the user. Accordingly, a large number of printing tests are required to find the optimum detection conditions, and it takes cost and time to determine the detection conditions.

  Although the technique described in Patent Document 1 can set a pass / fail standard level according to the required printing accuracy, there is a problem that an optimum detection condition cannot be set for each image to be printed.

  The present invention has been made in view of such circumstances, an image defect detection device capable of appropriately detecting an image defect by setting an optimal image defect detection condition according to a printing source image or an image feature amount of a printed matter, and It is an object to provide a method, an image recording apparatus, and a program.

  In order to achieve the above object, one aspect of the image defect detection apparatus includes an image defect addition setting unit that intentionally sets an image defect position to be added to the printing source image, and a position at which the image defect of the printing source image is added. An image feature amount acquisition means for acquiring the image feature amount, a defect added image generation means for generating a defect added image in which an image defect is added at a position set by the image defect addition setting means of the printing source image, and a print head A determination result acquisition unit that acquires a determination result as to whether or not an image defect that is acceptable as a printed matter is included in the printed matter on which the defect-added image is printed, and an image feature amount and a determination at the position where the image defect is added And a detection condition setting means for setting the detection condition of the image defect from the result.

  According to this aspect, a defect-added image in which an image defect is added to the printing source image is generated, and the image defect added to the printed material on which the defect-added image is printed by the print head is an image defect that is acceptable as a printed material. The image defect detection condition is acquired, and the image defect detection condition is set from the image feature amount at the position where the image defect is added and the determination result, so the optimum image defect detection condition is set according to the printing source image. can do.

  It is preferable that the image defect addition setting means sets the intensity of the image defect to be added, and the detection condition setting means sets the image defect detection condition from the intensity of the added image defect. Thereby, the detection conditions according to the intensity | strength of an image defect can be set.

  It is preferable to include an image defect detection unit that detects an image defect from a printed material on which the printing source image is printed by the print head based on the set detection condition. Thereby, an image defect can be appropriately detected from the printed material of the printing source image.

  It is preferable to include a determination unit that determines the quality of the printed material based on the detection result of the image defect detection unit. Thereby, the quality of printed matter can be determined appropriately.

  The print head is an inkjet head having a plurality of nozzles that eject ink, and includes a recording element information acquisition unit that acquires information on a plurality of nozzles that constitute the inkjet head, and the image defect addition setting unit includes a plurality of nozzles. Of these, it is preferable to set the position of an image defect to which the position of a nozzle having a history of occurrence of ejection abnormalities in the past is added. Thereby, an image defect can be added to a position with a high probability that an image defect will occur, and a detection condition can be set appropriately.

  The print head is configured by connecting a plurality of modules, and the defect-added image is printed by the print head in a single pass method, and includes module information acquisition means for acquiring information of the plurality of modules constituting the print head, The image defect addition setting means preferably sets the position of the image defect to which the connection position of the plurality of modules is added. Thereby, an image defect can be added to a position with a high probability that an image defect will occur, and a detection condition can be set appropriately.

  A required quality level acquisition means for acquiring a quality level representing the degree of quality required for the printed material, and an analysis means for analyzing the visibility level representing the degree of visibility of an image defect at each position of the printing source image, When the required quality level is the first quality level, the image defect addition setting means sets the position of the first visibility level to the position of the image defect in the printing source image, and is requested. If the quality level is a second quality level that is relatively lower than the first quality level, the second visibility level of the printing source image in which the visibility level is relatively higher than the first visibility level. It is preferable to set the position of the image defect to the position of the image defect. As a result, an image defect can be added to a position with a higher visibility level as the required quality level is relatively lower, so that detection conditions corresponding to the required quality level can be set.

  The image defect addition setting means preferably sets the position and length of a stripe intentionally added to the printing source image. Thereby, the detection condition according to the position and length of a stripe can be set.

  In order to achieve the above object, one aspect of the image defect detection apparatus is acceptable as a printed matter with respect to an added image defect of a printed matter on which a chart image to which an image defect is added at a predetermined position and intensity is printed. Determination result acquisition means for acquiring a determination result as to whether or not the image defect is present, image feature amount acquisition means for acquiring an image feature amount at a position where the image defect of the chart image is added, and strength of the added image defect And a detection condition setting means for setting a detection condition for the image defect from the image feature amount at the position where the image defect is added and the determination result.

  According to this aspect, the determination result of whether or not the image defect to which the printed image on which the chart image to which the image defect is added at the predetermined position and intensity is printed is added is an image defect acceptable as the printed material is obtained. The image defect detection conditions are set based on the intensity of the acquired image defect, the image feature quantity at the position where the image defect was added, and the determination result, so that the optimum image defect according to the image feature quantity is set. Detection conditions can be set.

  In order to achieve the above object, one aspect of the image recording apparatus includes an image defect addition setting means for setting a position of an image defect intentionally added to the printing source image, and a position for adding the image defect of the printing source image. An image feature quantity acquisition means for acquiring an image feature quantity, a defect addition image generation means for generating a defect addition image in which an image defect is added at a position set by the image defect addition setting means of the printing source image, and a defect addition image A printing unit that prints on a print medium by a print head and outputs it as a printed material, and a determination to obtain a determination result as to whether or not the image defect added to the printed material on which the defect-added image is printed is an image defect that is acceptable as a printed material A result acquisition unit; and a detection condition setting unit that sets a detection condition of the image defect from the image feature amount at the position where the image defect is added and the determination result. Image defect detection means for printing an image on a print medium by a print head and outputting it as a printed matter, and further detecting an image defect from the printed matter on which the printing source image is printed based on a set detection condition, and image defect detection Determination means for determining pass / fail of the printed matter on which the printing source image is printed based on the detection result of the means.

 In order to achieve the above object, one aspect of the image recording apparatus includes: a printing unit that prints a chart image to which an image defect is added at a predetermined position and intensity on a print medium by a print head and outputs the print image; A determination result acquisition means for acquiring a determination result as to whether or not an image defect is acceptable as a printed matter with respect to an image defect added to the printed matter on which the chart image is printed, and an image at a position where the image defect of the chart image is added Image feature amount acquisition means for acquiring feature amounts, and detection condition setting means for setting image defect detection conditions from the intensity of the added image defect, the image feature amount at the position where the image defect is added, and the determination result The printing means prints the original image on a printing medium by a print head and outputs it as a printed matter, and further prints based on the set detection condition. An image defect detecting means for detecting an image defect from the printed matter on which an image is printed, printing the original image on the basis of the detection result of the image defect detecting means and a determining means for the quality determination of a printing product of printing.

  According to this aspect, the chart image to which the image defect is added at a predetermined position and intensity is printed and output as a printed matter, and the image defect to which the printed matter is added is an image defect that is acceptable as the printed matter. As a result of the determination, the intensity of the added image defect, the image feature amount at the position where the image defect was added, and the detection condition of the image defect are set from the determination result. It is possible to set optimal image defect detection conditions.

  In order to achieve the above object, one aspect of the image defect detection method includes an image defect addition setting step for intentionally adding an image defect position to be added to the printing source image, and a position for adding the image defect of the printing source image. An image feature amount acquisition step for acquiring the image feature amount, a defect addition image generation step for generating a defect addition image in which an image defect is added to the position set in the image defect addition setting step of the printing source image, and a print head A determination result acquisition step for acquiring a determination result as to whether or not an image defect is acceptable as a printed matter for an image defect added to a printed matter on which a defect-added image is printed, and an image feature amount and a determination at a position where the image defect is added And a detection condition setting step for setting detection conditions for image defects from the results.

  According to this aspect, a defect-added image in which an image defect is added to the printing source image is generated, and the image defect added to the printed material on which the defect-added image is printed by the print head is an image defect that is acceptable as a printed material. The image defect detection condition is acquired, and the image defect detection condition is set from the image feature amount at the position where the image defect is added and the determination result, so the optimum image defect detection condition is set according to the printing source image. can do.

  In order to achieve the above object, one aspect of the image defect detection method is acceptable as a printed matter with respect to an added image defect of a printed matter on which a chart image to which an image defect is added at a predetermined position and intensity is printed. A determination result acquisition step of acquiring a determination result of whether or not the image defect is present, an image feature amount acquisition step of acquiring an image feature amount at a position where the image defect of the chart image is added, and an intensity of the added image defect A detection condition setting step of setting an image defect detection condition from the image feature amount at the position where the image defect is added and the determination result.

  According to this aspect, the determination result of whether or not the image defect to which the printed image on which the chart image to which the image defect is added at the predetermined position and intensity is printed is added is an image defect acceptable as the printed material is obtained. The image defect detection conditions are set based on the intensity of the acquired image defect, the image feature quantity at the position where the image defect was added, and the determination result, so that the optimum image defect according to the image feature quantity is set. Detection conditions can be set.

  A program for causing a computer to execute the image defect detection method is also included in this embodiment. Thereby, it is possible to set an optimal image defect detection condition.

  According to the present invention, it is possible to set an optimal image defect detection condition according to a printing source image. Further, it is possible to set an optimal image defect detection condition according to the image feature amount. Thereby, an image defect can be appropriately detected from a printed matter printed based on the printing source image.

FIG. 1 is a block diagram illustrating a schematic configuration of a streak detection apparatus. FIG. 2 is a block diagram illustrating a schematic configuration of the streak detection unit. FIG. 3 is a diagram illustrating an example in which the printing source image and the printing source image are divided for each region. FIG. 4 is a block diagram illustrating a schematic configuration of the detection condition setting unit. FIG. 5 is a flowchart illustrating a method for setting the streak determination condition of the detection condition setting unit. FIG. 6 is a diagram illustrating an example of a streak-added image. FIG. 7 is a diagram illustrating classification of image feature amounts acquired by the image feature amount calculation unit. FIG. 8 is a flowchart illustrating a method for detecting streaks in a printed material. FIG. 9 is a diagram showing the classification of the processing time and the expected image defect value calculated by the processing time / expected value evaluation unit. FIG. 10 is a diagram illustrating a table in which image feature amounts, processing times, and expected image defect values are associated with each other. FIG. 11 is a diagram illustrating the classification of the difference image contrast acquired by the image comparison unit, and the classification of the processing time and the expected image defect value calculated by the processing time / expectation value evaluation unit. FIG. 12 is a diagram illustrating a table in which the difference image contrast, the processing time, and the expected image defect value are associated with each other. FIG. 13 shows an example of a map in which regions having similar image feature amounts are grouped. FIG. 14 is a flowchart illustrating a method for setting the streak determination condition of the detection condition setting unit. FIG. 15 is a diagram illustrating the classification of the print application, the printing condition, the image feature amount, and the streak quality requirement. FIG. 16 is a block diagram illustrating a schematic configuration of the streak detection apparatus. FIG. 17 is a block diagram illustrating a schematic configuration of the detection condition setting unit. FIG. 18 is a flowchart illustrating a method for setting the streak determination condition of the detection condition setting unit. FIG. 19 is a diagram illustrating an example of a chart image. FIG. 20 is a block diagram illustrating a schematic configuration of the streak detection system. FIG. 21 is a diagram showing a schematic configuration of the ink jet recording apparatus. FIG. 22 is a perspective view showing a schematic configuration of the inkjet head. FIG. 23 is a plan view showing a schematic configuration of the inkjet head. FIG. 24 is a plan view showing the arrangement of the nozzles of the inkjet head. FIG. 25 is a block diagram illustrating a schematic configuration of the ink jet recording apparatus.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

<First Embodiment>
The streak detection apparatus 1 (an example of an image defect detection apparatus) according to the first embodiment generates a streak-added image (artificial simulation sample) in which streaks are intentionally added to a printing source image that is image data to be printed. Acquire the determination result of whether or not the streaks of the printed matter on which the streak-added image is generated is an acceptable image defect as the printed matter, and detect the streak of the printing source image from the image feature amount and the determination result of the streak position Set conditions.

[Overall configuration of streak detection device]
As shown in FIG. 1, the streak detection device 1 includes a streak detection unit 10, a detection condition setting unit 40, and a control unit 60. In addition, the streak detection device 1 is connected to a streak image output unit 70 outside the device.

  The streak detection unit 10 detects a streak of the printed material by comparing the printing original image and the read image of the printed material printed based on the printing original image. The detection condition setting unit 40 sets a streak determination condition for the print source image based on the determination result of the printed matter of the streaked image in which a streak is intentionally added to the print source image.

  The control unit 60 performs overall control of the streak detection unit 10 and the detection condition setting unit 40.

  The streak image output unit 70 includes a printing machine, prints the streak-added image generated by the detection condition setting unit 40, and outputs a printed matter (streaked image) on which the streak-added image is printed.

[Configuration of streak detector]
As shown in FIG. 2, the streak detection unit 10 includes a printing source image acquisition unit 12, a RIP (Raster Image Processor) processing unit 14, an image reading unit 16, a comparative color space conversion unit 18, an image registration unit 20, and a variation correction. Unit 22, image comparison unit 24, image feature amount calculation unit 26, processing time / expected value evaluation unit 28, determination region priority order assigning unit 30, determination region setting unit 32, streak determination unit 34, streak determination accumulation unit 36, and A pass / fail determination unit 38 is provided.

  The print source image acquisition unit 12 acquires a print source image of a print job that is a target of the streak detection process. Here, the print job refers to a unit of processing to be printed based on the print source image. FIG. 3A shows an example of the printing source image.

  The RIP processing unit 14 performs RIP processing on the acquired print source image. The RIP process is a conversion process for converting a print source image described in PDL (Page Description Language) or the like into raster format image data. A known method can be used for the RIP process.

  The image reading unit 16 includes a line scanner 16-1 and an image memory 16-2. The line scanner 16-1 reads a plurality of printed materials printed based on the printing source image, and a read image as a reading result. Are acquired and stored in the image memory 16-2. The image reading unit 16 may be input means for acquiring image data read by a line scanner outside the apparatus as a read image.

  The comparison color space conversion unit 18 converts both images into the same color space in order to compare the read image read by the image reading unit 16 and the printing source image subjected to the RIP processing in the RIP processing unit 14. . A known technique can be used for the color space conversion process.

  The image alignment unit 20 performs an alignment process on the read image and the print source image color-converted by the comparative color space conversion unit 18 with the correspondence determined by the printing conditions as an initial value. For the alignment process, a known technique such as template matching or phase limiting method can be used.

  The fluctuation correction unit 22 removes fluctuations in low-frequency pixel signals resulting from reading by the line scanner 16-1 from the read image that has been subjected to the alignment processing by the image alignment unit 20.

  The image comparison unit 24 divides the read image and the print source image into ROIs (Region of Interest), which are the minimum analysis units, and compares the read image and the print source image for each ROI, thereby matching the corresponding pixels. Is calculated, and the intensity of the difference signal (difference image contrast) and the corresponding position information are output. The area of each ROI is the same, and n ROIs are set. FIG. 3B is a diagram illustrating an example of the ROI set in the print source image. In this example, a total of 54 ROIs of 9 columns × 6 rows are set.

  The image feature quantity calculation unit 26 divides the color space-converted printing source image into ROIs similar to those of the image comparison unit 24, and calculates image feature quantities such as frequency characteristics and colors for each ROI. FIG. 3C is a diagram illustrating an example of the image feature amount for each ROI of the print source image, and the ROI represented by the same hatching indicates that the image feature amount is a close ROI.

  The processing time / expected value evaluation unit 28 detects the streak for each ROI of the read image based on the difference signal input from the image comparison unit 24 and its position information, and the image feature amount input from the image feature amount calculation unit 26. An estimate of the image defect detection time (processing time) indicating the time required to detect the image is calculated.

  In addition, the processing time / expected value evaluation unit 28 determines each ROI of the read image based on the difference signal input from the image comparison unit 24, its position information, and the image feature amount input from the image feature amount calculation unit 26. The expected image defect value indicating the possibility of the presence of the streak is calculated.

  The determination region priority order assigning unit 30 determines the priority order of the streak determination process described later for each ROI.

  The determination area setting unit 32 sequentially sets ROIs for performing the line determination process based on the priority order determined by the determination area priority order assigning unit 30 and outputs the ROI to the line determination unit 34. The determination area setting unit 32 includes a timer 32-1, and the timer 32-1 measures the time after the start of the line determination process for one printed matter. The determination area setting unit 32 ends the line determination process in the line determination unit 34 described later when a predetermined time has elapsed since the start of the line determination process.

  The streak determination unit 34 (an example of an image defect detection unit) performs a streak determination process on the ROI output from the determination region setting unit 32 of the read image. This streak determination process is performed based on a streak determination condition set in a streak setting unit 52 described later of the detection condition setting unit 40. Note that the streak determination process is performed by detecting image defect candidates existing in the read image based on the difference signal of the read image, and comparing the detected image defect candidates with the streak feature amount. This is processing for determining a similar image defect candidate as a streak. A streak is a linear image defect that occurs when the dot landing is shifted from the ideal position during printing, and includes a black streak with a higher density than the surroundings and a white streak with a lower density than the surroundings. In addition, streaks may occur because the size of the impacted dots at the time of printing is different from the surroundings. The black streaks that are generated because the dots are larger than the surroundings and the dots are smaller than the surroundings. There are white streaks with low density.

  Further, the streak determination unit 34 includes an input unit 34-1 and the user can input a streak determination standard from the input unit 34-1. For example, the streak determination criterion can be set in three stages: “strict”, “normal”, and “sweet”. If it is necessary to determine even a minute streak, the streak criterion is set to “strict”, and if a minute streak is not necessary, the streak criterion is set to “sweet”.

  The streak determination accumulation unit 36 aggregates the positions in the streak image determined by the streak determination unit 34, and determines the streak evaluation and the streak position of the read printed matter. The pass / fail determination unit 38 (an example of a determination unit) determines whether or not the printed product of the read image is suitable as a printed product to be shipped based on the streak evaluation and the streak position collected in the streak determination accumulation unit 36. )I do.

[Configuration of detection condition setting section]
As shown in FIG. 4, the detection condition setting unit 40 includes a printing source image input unit 42, a streak addition setting unit 44, a streak addition image generation unit 46, an image feature amount calculation unit 48, a streak addition image determination input unit 50, and A streak setting unit 52 is provided.

  The print source image input unit 42 is an input unit for acquiring a print source image of a print job that is a target of the line detection process. Here, the printing source image subjected to the RIP process is acquired from the RIP processing unit 14 of the streak detection unit 10. The printing source image input unit 42 includes input means such as a keyboard, a mouse, and a touch panel (all not shown), and the printing application and printing conditions of the printing source image are input by the user. The printing source image input unit 42 may use the printing source image acquisition unit 12 of the streak detection unit 10 in common.

  The streak addition setting unit 44 (an example of an image defect addition setting unit) is an input unit for setting the strength, length, and position of a streak that the user intentionally adds to the print source image. The streak addition setting unit 44 includes a monitor (not shown) for displaying a printing source image, a keyboard and mouse for inputting streak strength (color and thickness), length and position, a touch panel (all not shown), and the like. ing.

  The streak-added image generation unit 46 (an example of a defect-added image generation unit) adds streaks of intensity, length, and position set by the streak addition setting unit 44 to the print source image acquired by the print source image input unit 42. A streak-added image is generated. The streak-added image generated by the streak-added image generation unit 46 is input to a streak image output unit 70 outside the streak detection device 1. The streak image output unit 70 prints the streak-added image on a print medium with a print head (not shown) and outputs it as a printed matter. The streak image output unit 70 adds black streaks by generating large dots at positions where streaks are added or white streaks by generating small dots in the print head.

  The image feature amount calculation unit 48 (an example of an image feature amount acquisition unit) calculates the image feature amount of each area of the print source image. For example, the image is divided into ROI (Region of Interest) which is the minimum analysis unit, and the image feature amount for each ROI is calculated. Thereby, it is possible to know the distribution of the image feature amount of the entire printing source image. The image feature quantity calculation unit 48 may use the image feature quantity calculation unit 26 of the streak detection unit 10 in common.

  The streak-added image determination input unit 50 (an example of a determination result acquisition unit) is an input unit that inputs a determination result as to whether or not the added streak is an image defect that is acceptable as a printed matter, and includes a keyboard, a mouse, and a touch panel. (All not shown). The user visually recognizes the printed matter of the streak-added image printed by the streak image output unit 70, and inputs a determination result as to whether or not the added streaks are acceptable image defects as the printed matter.

  The streak setting unit 52 (an example of a detection condition setting unit) can accept the image feature amount of the printing source image acquired by the image feature amount calculation unit 48 and the added streak acquired by the streak added image determination input unit 50 as printed matter. Based on the information on whether or not the image is a defect, a streak determination condition (an example of a detection condition) of the printing source image is set. For example, the image feature amount is stored as a table in which information about whether or not the image defect is acceptable is associated.

[Straight line judgment condition setting method]
A method for setting the streak determination condition in the detection condition setting unit 40 will be described with reference to FIG.

  First, the printing source image input unit 42 acquires the printing source image subjected to the RIP process from the RIP processing unit 14 of the streak detection unit 10 (step S1). Further, the user sets the strength, length, and position of the stripe added to the print source image from the stripe addition setting unit 44 (step S2, an example of an image defect addition setting step).

  Next, the streak-added image generation unit 46 generates a streak-added image in which the streak of the intensity and length acquired in step S2 is added to the printing source image acquired in step S1 at the same position acquired in step S2. (Step S3, an example of a defect-added image generation step). FIG. 6 shows an example of a streak-added image. The streak-added image has a photographic area a, a photographic area b, a character area a, and a character area b. The photographic area a is a black line, a black line, a white line, and a white line. Three stripes of a certain stripe c are added.

  Subsequently, the streak image output unit 70 prints the streak-added image and outputs a printed matter on which the streak-added image is printed (step S4). The user visually recognizes the printed matter of the streak-added image output in step S4, and inputs whether or not the added streak is an image defect acceptable as a printed matter by the streaked-added image determination input unit 50. The streak setting unit 52 acquires the determination result (step S5, an example of a determination result acquisition step). In the example of the streak-added image shown in FIG. 6, whether or not each of the streak a, the streak b, and the streak c is acceptable is input.

  On the other hand, the image feature amount calculation unit 48 divides the print source image into ROIs that are the minimum analysis units, and acquires image feature amounts for each ROI (step S6, an example of an image feature amount acquisition step). The image feature amount calculation unit 48 acquires the hue, saturation, and brightness for the color, and the direction, contrast, and frequency for the frequency component as the image feature amount for each ROI.

  As shown in FIG. 7A, the image feature amount calculation unit 48 selects “low saturation”, “medium high saturation, cyan”, “medium high saturation” according to the stripe visibility, as shown in FIG. It is classified into seven levels of “degree, magenta”, “medium and high saturation, yellow”, “medium and high saturation, red”, “medium and high saturation, green”, and “medium and high saturation, blue”. Further, as shown in FIG. 7B, the lightness of the color has four levels of “0 to 20”, “20 to 40”, “40 to 60”, and “60 or more” according to the visibility rate of the stripe. Classify.

  Further, the image feature amount calculation unit 48 sets “−22.5 to 22.5 degrees” and “22.5 to 2” in accordance with the visibility ratio of the streak, as shown in FIG. It is classified into four levels of “67.5 degrees”, “67.5 to 112.5 degrees”, and “none”. The direction of the frequency component indicates an angle when the horizontal direction is set to 0 degrees when the image or character of the printed material is normally viewed. Further, when the direction of the frequency component is rotated by 180 degrees, the classification is performed in the same manner.

  In addition, the image feature amount calculation unit 48 “low” in contrast according to the stripe visibility as shown in FIG. 7D (less than 0.1 in terms of a value from a minimum of 0 to a maximum of 1). , “Medium” (0.1 to 0.25) and “High” (over 0.25). Furthermore, regarding the frequency, as shown in FIG. 7E, “low (less than 0.25 cycle / mm)”, “medium (0.25 to 1 cycle / mm)”, “high ( 1 level / mm)) ”.

  Based on the image feature value for each ROI, the image feature value calculation unit 48 uses the image feature value of the region a to which the streak a is added, the image feature value of the region b to which the streak b is added, and the region c to which the streak c is added. The image feature amount is acquired. Further, a wide range image feature amount a including the region a, the region b, and the region c, and the image feature amount b of the entire print source image are acquired.

  Finally, in the streak setting unit 52, based on the determination result of whether the added streaks acquired in step S5 is an image defect that is acceptable as a printed matter, and the image feature amount of the printing source image acquired in step S6, A streak determination condition is set (step S7, an example of a detection condition setting step). For example, the streak determination condition is determined for each combination of hue, saturation, and lightness for the colors shown in FIG. 7, and the direction, contrast, and frequency classifications for the frequency components.

  If it is desired to set the streak determination condition for other positions of the print source image, the streak addition setting unit 44 designates the strength, length and position of the streak to generate a new streak added image, and performs the same processing. Just do it.

  In this way, an image in which streaks are intentionally added to the printing source image is generated and output as a printed matter, and the user is allowed to determine whether or not the streaks added based on the printed matter are acceptable as a printed matter. Since the streak determination condition is set on the basis of the image feature amount at the position to which is added, it is possible to appropriately set the streak determination condition used for the streak determination processing of the printed matter on which the printing source image is printed. Accordingly, it is possible to appropriately perform the streak determination process for the printed matter on which the printing source image is printed.

[Streak detection method]
Next, a printed matter stripe detection method (an example of an image defect detection method) in the stripe detection apparatus 1 will be described with reference to FIG.

  First, the printing source image acquisition unit 12 acquires a printing source image (step S11). Subsequently, the RIP processing unit 14 performs RIP processing on the acquired print source image. The original image after the RIP process is converted into a color space (for example, L * a * b * space) for image comparison with the read image in the comparison color space conversion unit 18 (step S12).

  Next, the image feature amount calculation unit 26 divides the color space-converted printing source image into ROIs that are the minimum analysis units, and acquires image feature amounts for each ROI (step S13). The image feature amount calculation unit 26 acquires the hue, saturation, and lightness for the color and the direction, contrast, and frequency for the frequency component as the image feature amount for each ROI. These are classified in the same manner as the classification shown in FIG.

  Note that this processing is omitted by storing the image feature amount for each ROI of the printing source image acquired by the image feature amount calculation unit 48 in step S6 of the flowchart shown in FIG. 5 in a memory (not shown). It is also possible.

Next, the processing time / expected value evaluation unit 28 determines whether there is a streak and an image defect detection time (processing time) T1 _i indicating a time required for detecting a streak for each ROI of the printing source image. An expected image defect value E1 _i is calculated (step S14). i is an identification number i (i = 1 to N) for identifying each of the n ROIs. The processing time T1 _i is calculated based on the streak calculation complexity corresponding to the image feature amount (image defect visibility) of each ROI. The relationship between the image feature amount and the streak calculation complexity is stored in advance as a table. The expected image defect value E1 _i is calculated based on the image feature amount (image defect visibility) of each ROI.

As shown in FIG. 9A, the processing time / expected value evaluation unit 28 sets “A: long”, “B: slightly long”, “C: normal”, “D: slightly short” as the processing time T1 _i . And “E: short”. As the image defect expected value E1 _i, as shown in FIG. 9B, “I: high”, “II: slightly high”, “III: normal”, “IV: slightly low”, “V: low” Are classified into five levels.

It should be noted that the hue, saturation, 4th level lightness, 4th level frequency component direction, 3rd level frequency component contrast, and 3rd level frequency component, which are image feature values for each ROI, For all combinations of frequencies, a table in which the processing time T1 _i and the expected image defect value E1 _i are associated may be provided in the storage unit (not shown). In this case, the processing time / expected value evaluation unit 28 can read the processing time T1 _i and the expected image defect value E1 _i from this table in accordance with the image feature amount of each ROI.

FIG. 10 shows an example of this table. For example, color hue, saturation is “low saturation”, color brightness is “0-20”, frequency component direction is “none”, frequency component contrast is “low (less than 0.1)”, frequency If the frequency of the component is “low (less than 0.25 cycle / mm)”, the processing time T1 _i can be classified as “E: short”, and the expected image defect value E1 _i can be classified as “I: high”. . That is, when the image is close to black solid, the streak is very easy to determine and the visibility of the streak is high.

  The table shown in FIG. 10 creates an image of a combination of each level of color hue, saturation, color brightness, frequency component direction, frequency component contrast, and frequency component frequency, and a streak ( An expected image defect value is determined based on the visibility when an image defect occurs. In addition, an evaluation experiment using a streak detection test program is performed, and a processing time is determined by measuring a calculation time required to reach a required detection accuracy.

  Next, a streak determination condition is acquired from the streak setting unit 52 of the detection condition setting unit 40 (step S15). This streak determination condition is set in advance in the streak determination condition setting method described with reference to FIG. For example, a table in which the image feature amount is associated with information indicating whether the image defect is acceptable is acquired.

  Next, the image reading unit 16 reads a printed material that is a target of streak detection, and obtains a read image (step S16). The read image is converted into a color space (for example, L * a * b * space) for image comparison with the printing source image in the comparison color space conversion unit 18 (step S17).

  Further, the image alignment unit 20 performs alignment processing on the printing source image that has been color space converted in step S12 and the read image that has been color space converted in step S17, and the variation correction unit 22 performs alignment processing. Variations in low-frequency pixel signals resulting from reading are removed from the subsequent read image (step S18).

  Next, the image comparison unit 24 divides the original image and the read image after the alignment into ROIs, and calculates the intensity of the difference signal (difference image contrast) between corresponding pixels for each ROI (step S19). ). Since the difference signal between pixels includes positive and negative signs, the sum of squares of differences between pixels is used as the intensity of the difference signal here.

  As shown in FIG. 11A, the image comparison unit 24 “A: large”, “B: slightly large”, “C: normal”, “D: slightly” It is classified into five levels, “small” and “E: small”.

Next, the processing time / expected value evaluation unit 28 calculates the time necessary for detecting the streak for each ROI of the read image based on the intensity of the difference signal (difference image contrast) calculated by the image comparison unit 24. The image defect detection time (processing time) T2 _i shown and the image defect expectation value E2 _i showing the possibility of the presence of streaks are calculated (step S20).

Processing time and the expected value evaluation section 28, the processing time T2 _i, as shown in FIG. 11 (b), the processing time is in the descending order "A: long", "B: somewhat longer", "C: normal", It is classified into five levels, “D: Slightly short” and “E: Short”. Further, as shown in FIG. 11C, the expected image defect value E2 _i is “I: high”, “II: slightly high”, “III: normal”, “IV: slightly low” in descending order of the expected value. , “V: low” is classified into five levels.

The processing time / expected value evaluation unit 28 stores, as shown in FIG. 10, a table in which processing time T2 _i and image defect expected value E2 _i are associated with each other for five levels of differential image contrast for each ROI (not shown). ) May be prepared.

Here, the processing time / expected value evaluation unit 28 adjusts the processing time T2 _i and the image defect expected value E2 _i to be assigned to each difference image contrast in accordance with a streak determination criterion input in advance.

As shown in FIG. 12A, when the streak determination criterion is “strict”, that is, when it is necessary to determine even a small streak, the ROI with the difference image contrast of D level (slightly small) is the threshold for streak determination. It becomes. Therefore, since precise calculation is required in the D-level ROI streaking process, the D-level ROI is assigned the A level (long) for the processing time T2 _i and the image defect expectation value E2 _i is the III level (normal). ) Is assigned. In addition, since a precise calculation is required for an ROI having a difference image contrast of E level (small), a B level (slightly long) is assigned to the processing time T2 _i . Further, since the ROI having the difference image contrast of A level (large) to C level (normal) is considered to have minute streaks, the expected image defect value is high at I level (high) or II level (slightly high). E2 _i is assigned.

Also, as shown in FIG. 12B, when the streak determination criterion is “sweet”, that is, when a fine streak need not be determined, an ROI whose differential image contrast is B level (slightly large) It becomes a threshold value. Therefore, it requires precise calculation in the stripe determination process of the ROI of the B level, the processing time T2 _i assigned A levels (long) is, the image defect expectation E2 _i III level (usually) is assigned. In addition, for ROI having a differential image contrast of C level (normal) to E level (small), it is considered that there are not so many fine streaks, so image defects with low IV level (slightly low) or V level (low). Expected value is assigned.

  Also, as shown in FIG. 12C, when the streak determination criterion is “normal”, the ROI with the C level (normal) difference image contrast is the threshold for streak determination, and therefore the processing time for the C level ROI Since an accurate calculation is required, A level (long) is assigned, and an expected image defect value is assigned III level (normal). In addition, for ROIs having differential image contrasts of A level (large) and B level (slightly large), high expected image defect values of I level (high) and II level (slightly high) are assigned. Further, for ROIs having a differential image contrast of D level (slightly small) and E level (small), an image defect expectation value having a low IV level (slightly low) or V level (low) is assigned.

Subsequently, the processing time / expected value evaluation unit 28 is based on the processing time T1 _i and the expected image defect value E1 _{i for} each ROI based on the image feature amount calculated in step S14, and the difference signal calculated in step S20. From the processing time T2 _i and the expected image defect value E2 _{i for} each ROI, the final (total) processing time T _i and the expected image defect value E _i are calculated (step S21).

For example, a hue of a certain ROI, saturation is “low saturation”, color brightness is “0 to 20”, frequency component direction is “none”, and frequency component contrast is “low (less than 0.1)” If the frequency of the frequency component is “low (less than 0.25 cycle / mm)”, as shown in FIG. 10, “E: short” for the processing time T1 _{i and} “expected image defect value E1 _i ” I: High ”.

If the ROI streak criterion is “normal” and the difference image contrast is “C: normal”, as shown in FIG. 12C, “A: long” for the processing time T2 _i. The expected image defect value E2 _i is classified as “III: normal”.

Processing time and the expected value evaluation unit 28, the overall processing time T _i of this ROI, the processing time T1 _i "E: short" and the processing of the time T2 _i "A: long" the longer the value of the " a: a long ", the overall image defect expectation _{E i} is the product" I × III "with E1 _i and E2 _i.

Similarly, the processing time T _i and the expected image defect value E _i are calculated for all ROIs.

Next, the determination region priority order assigning unit 30 assigns a priority order for performing the streak determination process for each ROI of the read image (step S22). In the present embodiment, a higher priority order is assigned to an ROI having a larger overall image defect expectation value E _i for each ROI calculated in step S11.

Further, the quotient obtained by dividing the image defect expected value E _i by the processing time T _i , that is, the image defect detection efficiency V _i = E _i / T _i which is the image defect expected value per unit processing time is calculated, and this image defect detection is performed. Higher priority orders may be assigned to ROIs with higher efficiency Vi.

  Based on this priority order, the determination area setting unit 32 sets an ROI in which the streak determination unit 34 performs streak determination among all the ROIs of the read image (step S23).

The streak determination unit 34 sequentially performs streak determination on the ROI set in the determination region setting unit 32 based on the streak determination condition set in the streak setting unit 52 of the detection condition setting unit 40 (step S24). For example, an acceptable image defect associated with an image feature quantity that matches or is similar to the image feature quantity of the corresponding ROI from a table in which the image feature quantity is associated with information on whether or not the image feature quantity is acceptable. Whether or not it is acceptable is not determined as a streak, and when it is not permissible, it is determined as a streak. Here, the determination area setting unit 32 measures the time from the start of the streak determination process by the timer 32-1. If the inspection time has elapsed since the start of the streak determination process, the streak determination process in the streak determination unit 34 is terminated. This inspection time is determined in advance from the cycle of printing the printed matter by the print job. Accordingly, the ROI on which the streak determination process is performed in the streak determination unit 34 has the maximum sum ΣE _i of the image defect expected value E _{i and} the total sum ΣT _i of the processing time T _i equal to or shorter than the inspection time.

  The line determination results in the line determination unit 34 are collected in the line determination accumulation unit 36, and the line determination accumulation unit 36 determines the line evaluation and the line position of the printed product of the read image. The pass / fail determination unit 38 determines pass / fail of the printed matter of the read image based on the aggregated line information (step S25). In the present embodiment, the pass / fail of the printed matter is determined based on the aggregated stripe information, but when the stripe is detected in the stripe determination process of the stripe determination unit 34, the printed matter of the read image is determined to be a rejected product. An embodiment is also possible.

  Thereafter, the pass / fail determination unit 38 determines whether or not the streak determination process has been performed for all printed matter of the print job (step S26). If there is a printed matter that has not been subjected to the streak determination process, the process returns to step S16 and the same process is performed. If all printed matter is finished, the streak detection process is finished.

  As described above, according to the present embodiment, a streak-added image in which streaks are intentionally added to the printing source image is generated, and streaks added to the printed matter on which the streaks-added image is printed are image defects that can be accepted as a printed matter. The determination result of whether or not, the streak determination condition is set from the image feature amount of the streak position and the determination result, and the streak determination process is performed based on this determination condition. Various conditions can be set, and the streak determination process of the printed matter can be appropriately performed.

  In the present embodiment, the streak detection is described as an example of the image defect of the printed matter, but an image defect other than the streak can be detected. Possible image defects include a state where ink is not applied in the correct amount at the correct position on the paper, and a state where something other than ink is attached to the medium.

Examples of the state where the ink is not applied in the correct amount at the correct position on the paper include the following.
-White streaks: Insufficient ink or not applied, and the shape is long in the predetermined direction, and the length in the direction perpendicular to the predetermined direction is about the image resolution.-Black streaks: The ink is excessively applied and the shape. Is long in the predetermined direction, and the length in the direction perpendicular to the predetermined direction is about the resolution of the image. Secondary color streaks, multi-color streaks: At least one of the plurality of inks is insufficient or excessive, and the shape is in the predetermined direction. The length in the direction perpendicular to the specified direction is about the resolution of the image.Character missing: Some ink of the ink constituting the character is insufficient or not attached. Extra ink adhering to the character: in the character area. Characters cannot be recognized due to excess ink adhering. Ink dripping: Ink adheres to a place where ink is not originally present, and the shape is substantially circular. Banding: Insufficient ink or excessive state continues, insufficient Or, the period of excessive ink change is relatively low frequency / unevenness: Insufficient or excessive state of ink is continuous, the period of insufficient or excessive ink change is relatively high frequency / color reproduction: From target color reproduction There is an unacceptable amount (color difference) misalignment. On the other hand, a state where an object other than ink adheres to the medium includes the following.
- paper dust: foreign matter garbage powdered paper is deposited on the printed matter: The foreign matter other than paper are attached onto the printed material, in the present embodiment, the sum oT _i processing time T _i is examined For the ROI exceeding the time, streak determination processing is not performed, but when ΣT _i > inspection time, the streak determination processing is replaced with processing with a small amount of computation, so that all the inspection time is not exceeded. The ROI streak determination process may be terminated.

  In the present embodiment, the streak determination process is performed in the order of the ROI having the highest priority order. However, if the streak determination process can be performed within the inspection time for the ROI having the higher priority order, the order in which the streak determination process is performed is the priority order. It is not limited to. For example, an ROI streak determination process with the highest priority order may be performed after the ROI streak determination process with the second highest priority order is performed. That is, when there is an ROI for which the streak determination process cannot be performed within the inspection time, it is sufficient that the priority order of the ROI is lower than the ROI for which the streak determination process has been performed.

  Further, a priority order is assigned to each ROI, and the streak determination process is performed for each ROI in the assigned priority order. However, the image feature quantity is divided into regions that are close (image feature quantities are similar), and this image feature quantity Alternatively, a map in which regions close to each other are created together, a priority order is assigned to each region having a similar image feature amount, and a streak determination process may be performed for each region in the assigned priority order. Here, the image feature amount used to group the regions includes the hue, saturation, color brightness, frequency component direction, frequency component contrast, and frequency component frequency shown in FIG. An embodiment using at least one is also possible.

FIG. 13 shows an example of a map in which regions having similar image feature values are grouped together based on the image feature values for each ROI of the printing source image shown in FIG. Here, the region is divided into six regions of region R _a , region R _b , region R _c , region R _d , region R _e , and region R _f . Based on this map, the processing time / expected value evaluation unit 28 calculates the processing time T _i and the image defect expected value E _i for each of the regions R _{a to} R _f , and the determination region priority order assigning unit 30 calculates the priority order. Can be given.

  As described above, even when the printing source image is divided for each region having a similar image feature amount, it is possible to detect an image defect with high accuracy within a certain time.

<Second Embodiment>
A method for setting the streak determination condition according to the second embodiment will be described with reference to FIG. In addition, the same code | symbol is attached | subjected to the part which is common in the flowchart shown in FIG. 5, and the detailed description is abbreviate | omitted. In the second embodiment, a quality level (streaks quality request) representing the degree of quality required for the printed material is calculated according to the characteristics of the printing source image, and the position where the streaks are added is determined according to the streaks quality request. To do.

  First, a printing source image is acquired in the printing source image input unit 42 (step S1).

  Next, the image feature amount calculation unit 48 (an example of an analysis unit) acquires image feature amounts from the viewpoint of streak visibility for each ROI of the printing source image, and the degree of visibility of the streaks at each position of the printing source image. Is evaluated (step S31). Here, the hue, saturation, and lightness for the color, and the direction, contrast, and frequency for the frequency component shown in FIG.

  Subsequently, the image feature quantity calculation unit 48 obtains image feature quantities (image feature quantities that change the value of the printed matter depending on the presence or absence of streaks) from the viewpoint of handling the streak quality, and evaluates the entire image of the printing source image. (Step S32).

  As this image feature amount, as shown in FIG. 15A, the color range used, the ratio of character area / image area, the number / size of human faces, and the area ratio of substantially uniform area as shown in FIG. , And identity in the image. As the image feature amount, at least one of a color range to be used, a character area / image area ratio, the number / size of a person's face, an area ratio of a substantially uniform area, and identity in an image is used. Embodiments are possible.

  Here, the area ratio of the substantially uniform region is the ratio of the solid area in the image. The identity in the image is the ratio at which other regions having similar characteristics exist in the image. For example, in the case where a plurality of the same images are imposed in one image, this ratio becomes high.

  In addition, although the entire image of the printing source image is evaluated here, a wide area that is a main area of the printing source image may be evaluated. For example, a wide range of image feature amount a shown in FIG. 6 may be used.

  Next, the streak setting unit 52 acquires the printing application and printing conditions of the printed material on which the printing source image is printed (step S33). The printing application and printing conditions may be input by the user in the input unit of the printing source image input unit 42, or acquired from other input unit (not shown) as additional information (printing job information) of the printing source image. May be.

  As shown in FIG. 15B, as an example of the printing application, it is classified into three types of “catalog”, “flyer”, and “photo book” as major classifications. Further, each of the large classifications is classified into three types of “HI”, “MID”, and “LOW” in descending order of required quality as medium classifications. Note that the printing application may be classified into at least two types of “catalog”, “flyer”, and “photo book”.

  Further, as shown in FIG. 15C, as an example of the printing conditions, the paper is classified by the type and thickness of the paper. Here, the paper types are classified into three types: “coated paper”, “matte paper”, and “semi-coated paper”. Further, each paper is classified into three types, “thick”, “normal”, and “thin”. In addition, as a printing condition, the aspect which uses at least one among the kind and thickness of a paper is also possible.

  Next, in the streak setting unit 52 (an example of the required quality level acquisition unit), based on the image feature amount related to the handling of the streak quality acquired in step S32 and the printing application and printing conditions acquired in step S33, A quality level (streaks quality request) representing the degree of quality required in the printed material on which the printing source image is printed is calculated (step S34). Here, as shown in FIG. 15D, the streak quality requirements are “I: high”, “II: slightly high”, “III: normal”, “IV: slightly low”, and “V: low”. Classify into 5 levels.

  For example, if the ratio of the character area / image area of the image feature amount is higher, the higher the image area ratio, the higher the streak quality requirement. Also, for printing applications, streak quality requirements are likely to be higher for photo books than for flyers. In terms of printing conditions, it is considered that the streak quality requirement is higher for thick paper than for thin paper. Therefore, considering these factors, the streak quality requirements are classified into five levels.

  The streak quality request may be calculated based on at least one of the image feature amount, the printing application, and the printing conditions related to the handling of streak quality.

  Further, the streak setting unit 52 determines a position to add a streak of the printing source image based on the streak quality request and the visibility level of each position calculated in step S31 (step S35). Here, the position where the streak is added is set to a position with a lower visibility level (a position where the streak is less visible) as the streak quality requirement is higher, and a position with a higher visibility level (a streak is more visible) as the streak quality requirement is lower. Position). That is, when the quality requirement is the first quality level, the position of the first visibility level is set to the streak position in the printing source image, and the required quality requirement is relative to the first quality level. If the second quality level is lower than the first visibility level, the position of the second visibility level that is relatively higher than the first visibility level is set as the streak position.

  For example, if the streak quality request is “I: high”, the streak visibility is set to a relatively low position. If the streak quality requirement is “II: Slightly high”, the streak visibility is set to a relatively low position. Conversely, if the streak quality requirement is “V: low”, the streak visibility is set to a relatively high position. If the streak quality requirement is “IV: Slightly low”, the streak visibility is set to a relatively high position.

  A streak image with a streak added to the streak position determined in this way is generated (step S3), and is output as a printed matter (step S4). The user visually recognizes this printed matter and inputs whether or not the added streaks are acceptable image defects as the printed matter through the streaked added image determination input unit 50 (step S5).

  Finally, in the streak setting unit 52, based on the determination result of whether the added streaks acquired in step S5 is an image defect that is acceptable as a printed matter, and the image feature amount of the printing source image acquired in step S31, A streak determination condition is set (step S7).

  Thus, the higher the streak quality requirement is, the lower the streak visibility is, and the lower the streak quality requirement is, the higher the streak visibility is. Thus, the streak determination condition can be set with a streak that is difficult to see when the streak quality requirement is high, and the streak determination condition can be set with a streak that is easy to see when the streak quality requirement is low.

<Third Embodiment>
The streak detection apparatus 2 (an example of an image defect detection apparatus) according to the third embodiment acquires a determination result as to whether or not a streak of a printed matter on which a chart image is printed is an image defect that is acceptable as a printed matter. A streak detection condition is set from the image feature quantity and the determination result at the position.

[Overall configuration of streak detection device]
As shown in FIG. 16, the streak detection device 2 includes a streak detection unit 10, a control unit 60, and a detection condition setting unit 80. The streak detection unit 10 and the control unit 60 have the same configuration as the streak detection unit 10 and the control unit 60 of the streak detection device 1.

[Configuration of detection condition setting section]
As shown in FIG. 17, the detection condition setting unit 80 according to the second embodiment includes an image feature amount calculation unit 48, a streak addition image determination input unit 50, a streak setting unit 52, and a chart image input unit 82. Yes.

  The image feature amount calculation unit 48, the streak addition image determination input unit 50, and the streak setting unit 52 are the same as the image feature amount calculation unit 48, the streak addition image determination input unit 50, and the streak setting unit 52 of the detection condition setting unit 40. It is the composition.

  The chart image input unit 82 is an acquisition unit that acquires a chart image with a streak added at a predetermined position and intensity. Here, the chart image is stored in a memory (not shown), and the chart image input unit 82 functions as a reading unit that reads the chart image from the memory. The chart image input unit 82 outputs the acquired chart image to the streak image output unit 70 outside the streak detection device 2.

[Straight line judgment condition setting method]
A method for setting the streak determination condition in the detection condition setting unit 80 will be described with reference to FIG.

  First, a chart image is acquired in the chart image input unit 82 (step S41). Here, the chart image stored in the memory (not shown) is read as described above.

  As shown in FIG. 19, the chart image is composed of areas of black (low saturation), cyan, magenta, yellow, red, green, and blue. Each color area is composed of three areas, a gradation area where the density gradually increases from the left side to the right side in the figure, a fine stripe pattern area, and a coarse stripe pattern area.

  In addition, the line d is black in the black (low saturation) area, the line e is in the cyan area, the line f is in the magenta area, the line g is in the yellow area, and the line h is in the red area. However, a streak j is added to the green region and a streak k is added to the blue region at a predetermined position and intensity.

  Next, the streak image output unit 70 outputs (prints) the chart image (step S42).

  The user visually recognizes the printed matter of the chart image output in step S42, and inputs whether or not the streaks added to the respective areas are image defects that can be accepted as the printed matter, using the streaked added image determination input unit 50. The streak setting unit 52 acquires the determination result (step S43, an example of a determination result acquisition step). For the gradation area, the determination as to whether or not it is acceptable may differ depending on the density. Therefore, a boundary between an acceptable density and an unacceptable density may be designated.

  On the other hand, the image feature amount calculation unit 48 divides the chart image into ROIs that are the minimum analysis units, and acquires image feature amounts for each ROI (step S44, an example of an image feature amount acquisition step). The image feature amount calculation unit 48 acquires the hue, saturation, and brightness for the color, and the direction, contrast, and frequency for the frequency component as the image feature amount for each ROI. These are classified in the same manner as the classification shown in FIG. Note that the image feature amount calculation unit 48 may read the image feature amount for each ROI of the chart image stored in advance in a memory (not shown) from the memory.

  The image feature amount calculation unit 48 acquires the image feature amount of each region to which the lines d to k are added based on the image feature amount for each ROI.

  Finally, the streak setting unit 52 sets a streak determination condition based on the determination result acquired in step S43 and the image feature amount of the printing source image acquired in step S44 (step S45, detection condition setting step). One case).

  In this way, a chart image to which streaks are added at a predetermined position and intensity is printed by the print head, and a determination result as to whether the streaks of the printed material are acceptable image defects as the printed material is acquired. Since the streak detection condition is set based on the image feature quantity at the streak position and the determination result, the streak determination condition used for the streak determination process for the printed matter can be set appropriately. Accordingly, it is possible to appropriately perform the streak determination process for the printed matter on which the printing source image is printed. Further, the same processing may be performed for a plurality of chart images having different streaks.

  The streak detection method and the streak determination condition setting method described above are configured as a program that causes a computer to execute each process, and a non-transitory recording medium (for example, a CD-ROM (Compact Disk-Read Only Memory) that stores the program. )) Can also be configured.

<Fourth Embodiment>
Even when a part of the functions of the streak detection apparatus 1 and the streak detection apparatus 2 is arranged on the server, it is possible to set the optimum streak determination condition according to the print source image and perform the streak determination process. . Here, as an example, a streak detection system in which some functions of the streak detection device 1 are arranged in a server will be described.

  A streak detection system 90 shown in FIG. 20 includes a streak detection device 92 and a detection condition setting server 94. In addition, the same code | symbol is attached | subjected to the part which is common in the streak detection apparatus 1 shown in FIG. 1, and the detection condition setting part 40 shown in FIG. 4, and the detailed description is abbreviate | omitted.

  The streak detection device 92 includes a streak addition setting unit 44 and a streak addition image determination input unit 50 in addition to the streak detection unit 10 and the control unit 60. The detection condition setting server 94 includes a printing source image input unit 42, a streak-added image generation unit 46, an image feature amount calculation unit 48, and a streak setting unit 52.

  The streak detection device 92 and the server 92 are communicably connected via a network such as a LAN (Local Area Network) or a WAN (Wide Area Network), and the streak detection device 92 and the server 92 transmit and receive information using a predetermined protocol. Processing similar to that of the detection apparatus 1 can be performed. Therefore, it is possible to perform the streak determination process by setting the optimum streak determination condition according to the printing source image.

  In FIG. 20, one streak detection device 92 is described for one detection condition setting server 94, but a plurality of streak detection devices 92 are configured to be accessible to one detection condition setting server 94. The detection condition setting server 94 may be shared by a plurality of streak detection devices 92. As a result, it is possible to perform the streak determination process by setting the optimum streak determination condition according to the printing source image while reducing the size of the streak detection device 92.

  In the streak detection system, a mode in which a part of the function is shared by the server is not limited to the example illustrated in FIG. 20, and it is possible to appropriately determine which function is to be shared by the server.

<Fifth Embodiment>
The streak detection apparatuses 1 and 2 and the streak detection system 90 can be combined with various printing means to constitute a printing machine. Here, an ink jet recording apparatus (an example of an image recording apparatus) to which the streak detection apparatus 1 is applied will be described as an example.

[Overall configuration of inkjet recording apparatus]
The ink jet recording apparatus 100 ejects ink of four colors, cyan (C), magenta (M), yellow (Y), and black (K), onto a sheet P (an example of a print medium) that is a sheet of paper. This is a printing machine for recording images. General-purpose printing paper is used for the sheet and water-based ink is used for the ink. Here, the general-purpose printing paper is not so-called ink-jet dedicated paper but means paper mainly composed of cellulose such as coated paper used for general offset printing. Further, the water-based ink refers to an ink in which a coloring material such as a dye or a pigment is dissolved or dispersed in water and a water-soluble solvent.

  As shown in FIG. 21, the ink jet recording apparatus 100 includes a transport drum 110, a recording drum 112, an ink jet head unit 120, an inline sensor 140, a chain gripper 150, a heater 160, a stamper 170, a paper discharge table 180, and the like. The

  The transport drum 110 transports the paper P fed from a paper feed unit (not shown) and delivers it to the recording drum 112.

  The recording drum 112 functions as a sheet holding unit that holds the sheet P and also functions as a sheet conveying unit that conveys the sheet P. The recording drum 112 receives the paper P from the transport drum 110 and transports the paper P to the chain gripper 150. The recording drum 112 is formed in a cylindrical shape, and is rotated by being driven by a motor (not shown) serving as a driving unit. A gripper (not shown) is provided on the outer peripheral surface of the recording drum 112, and the leading edge of the paper P is gripped by this gripper. The recording drum 112 conveys the paper P to the chain gripper 150 while winding the paper P around the peripheral surface by gripping and rotating the leading edge of the paper P with the gripper.

  Further, the recording drum 112 has a large number of suction holes (not shown) formed in a predetermined pattern on the peripheral surface thereof. The sheet P wound around the peripheral surface of the recording drum 112 is conveyed while being sucked and held on the peripheral surface of the recording drum 112 by being sucked from the suction hole. Thereby, the paper P can be conveyed with high flatness.

  The inkjet head unit 120 includes an inkjet head 122C that ejects cyan (C) ink droplets by an inkjet method, an inkjet head 122M that ejects magenta (M) ink droplets by an inkjet method, and yellow (Y) ink droplets. This is a printing unit that includes an inkjet head 122Y that ejects ink by an inkjet method and an inkjet head 122K that ejects black (K) ink droplets by an inkjet method. The inkjet heads 122C, 122M, 122Y, and 122K are arranged at regular intervals along the conveyance path of the paper P by the recording drum 112.

  Each of the inkjet heads 122C, 122M, 122Y and 122K is composed of a line head, and has a length corresponding to the maximum paper width. Each of the inkjet heads 122C, 122M, 122Y, and 122K is disposed such that the nozzle surface (surface on which the nozzles are arranged) faces the circumferential surface of the recording drum 112.

  Each of the inkjet heads 122C, 122M, 122Y, and 122K discharges ink droplets from the nozzles formed on the nozzle surface toward the recording drum 112, so that the single-pass method is applied to the paper P conveyed by the recording drum 112. Record an image with.

  The inline sensor 140 functions as an image reading unit that reads an image recorded on the paper P. The inline sensor 140 is installed on the downstream side of the inkjet head unit 120 with respect to the conveyance direction of the paper P by the recording drum 112, and is configured by, for example, a line scanner. The in-line sensor 140 reads images recorded by the inkjet heads 122C, 122M, 122Y and 122K from the paper P conveyed by the recording drum 112.

  The chain gripper 150 is a paper transport unit that transports the paper P from the recording drum 112 to the paper discharge stand 180. The chain gripper 150 mainly includes a first sprocket 150a installed in the vicinity of the recording drum 112, a second sprocket 150b installed in the vicinity of the paper discharge table 180, and the first sprocket 150a and the second sprocket 150b. The endless chain 150c is wound around, a plurality of chain guides (not shown) for guiding the travel of the chain 150c, and a plurality of grippers 150d attached to the chain 150c with a certain interval.

  The first sprocket 150a, the second sprocket 150b, the chain 150c, and the chain guide are each configured as a pair, and are disposed on both sides of the paper P in the width direction. The gripper 150d is installed over a chain 150c provided as a pair.

  The first sprocket 150a is installed close to the recording drum 112 so that the paper P delivered from the recording drum 112 can be received by the gripper 150d. The first sprocket 150a is rotatably supported by being supported by a bearing (not shown), and is connected to a motor (not shown). 150c wound around the first sprocket 150a and the second sprocket 150b travels by driving this motor.

  The second sprocket 150 b is installed in the vicinity of the paper discharge table 180 so that the paper P received from the recording drum 112 can be collected by the paper discharge table 180. That is, the installation position of the second sprocket 150b is the end of the transport path of the paper P by the chain gripper 150. The second sprocket 150b is pivotally supported by a bearing (not shown) and is rotatably provided.

  The chain 150c is formed in an endless shape and is wound around the first sprocket 150a and the second sprocket 150b. The chain guide is arranged at a predetermined position and guides the chain 150c to travel along a predetermined route.

  A plurality of grippers 150d are attached to the chain 150c with a constant interval. The mounting interval of the gripper 150d is set in accordance with the receiving interval of the paper P from the recording drum 112. That is, it is set according to the receiving interval of the paper P from the recording drum 112 so that the paper P sequentially delivered from the recording drum 112 can be received from the recording drum 112 at the same timing.

  The heater 160 is installed inside the chain gripper 150 and blows hot air on the surface of the paper P conveyed by the chain gripper 150 to perform a drying process.

  The stamper 170 is disposed on the downstream side of the heater 160 in the transport direction of the paper P transported by the chain gripper 150. The stamper 170 attaches ink to the leading edge of the paper P determined to be a rejected product based on the pass / fail determination result of the streak detection device 1.

  The paper discharge stand 180 stacks and collects the paper P conveyed by the chain gripper 150. The paper discharge table 180 is provided with a paper pad (not shown) such as a front paper pad, a rear paper pad, or a horizontal paper pad so that the sheets P are stacked in an orderly manner.

  Further, the paper discharge tray 180 is provided so as to be lifted and lowered by a paper discharge tray lifting / lowering device (not shown). The discharge platform lifting device is controlled in conjunction with the increase / decrease of the sheets P stacked on the sheet discharge platform 180 so that the uppermost sheet P is always positioned at a certain height. The paper table 180 is moved up and down.

  In the ink jet recording apparatus 100 configured as described above, the paper P delivered from the transport drum 110 is first received by the recording drum 112. The recording drum 112 conveys the paper P by gripping and rotating the front end of the paper P with a gripper. At this time, the paper P is sucked from the suction hole of the recording drum 112 and sucked and held on the outer peripheral surface of the recording drum 112.

  The paper P is transported in this state and passes through the inkjet heads 122C, 122M, 122Y, and 122K. Then, during the passage, ink droplets of each color of C, M, Y, and K are ejected from the inkjet heads 122C, 122M, 122Y, and 122K onto the surface, and a color image is drawn on the surface.

  The paper P on which an image is recorded by the ink jet heads 122C, 122M, 122Y, and 122K then passes through the inline sensor 140. Then, an image recorded on the recording surface when the inline sensor 140 passes is read. When reading is performed, the reading is performed in a state where the recording drum 112 is sucked and held, so that the reading can be performed with high accuracy. Thereafter, the sheet P is delivered to the chain gripper 150 after the suction is released.

  When the chain gripper 150 drives a motor (not shown) connected to the first sprocket 150a, the chain 150c travels. The chain 150c travels at the same speed as the circumferential speed of the recording drum 112. Further, the timing is adjusted so that the paper P delivered from the recording drum 112 can be received by each gripper 150d.

  The sheet P received by the gripper 150d and conveyed by the chain gripper 150 is heated by the heater 160 while the recording surface is in sliding contact with the upper surface of a guide plate (not shown). As a result, the ink applied to the recording surface is dried.

  In addition, the paper P determined to be a rejected product has ink attached to the edge by the stamper 170 while being conveyed to the chain gripper 150.

  The chain gripper 150 opens the paper P on the paper discharge tray 180 and stacks the paper P on the paper discharge tray 180. The paper discharge table 180 is raised and lowered so that the uppermost sheet P is always positioned at a certain height.

  When viewed from the stacking direction, the bundle of sheets P stacked on the paper discharge tray 180 is easily rejected because the ink from the stamper 170 adheres to the rejected sheets P. Can be specified.

[Configuration of inkjet head]
Here, the configuration of the inkjet heads 122C, 122M, 122Y, and 122K will be described. In addition, since the structure of each inkjet head 122C, 122M, 122Y, and 122K is the same, the structure is demonstrated as the inkjet head 122. FIG.

  As shown in FIG. 22, the inkjet head 122 (an example of a print head) connects a plurality (16 in the present embodiment) of head modules 124-i (i = 1, 2,..., 16) in a line. Configured together (linked).

  Each head module 124-i has the same structure, and is connected to one line by being attached to the linear bar frame 128. The bar frame 128 includes a mounting portion (not shown) for mounting each head module 124-i, and the head module 124-i is detachably mounted on this mounting portion. Each head module 124-i is attached to the bar frame 128, so that the nozzle surfaces provided at the tips are connected in a line to form one nozzle surface 126.

  23 and 24, the arrow Y direction is the conveyance direction of the paper P, and the arrow X direction is the width direction of the paper P (the axial direction of the recording drum 112). As shown in FIG. 23, the nozzle surface 126 of the inkjet head 122 has a rectangular shape as a whole, and is provided with a belt-like nozzle arrangement region 126A in the central portion. The nozzle N is provided in the nozzle arrangement region 126A.

  Further, as shown in FIG. 24, the nozzles N are arranged in a matrix. More specifically, the nozzles N are arranged at a constant pitch along a straight line x parallel to the X direction, and the nozzles N are arranged at a constant pitch along a straight line y inclined by a predetermined angle (α) with respect to the straight line x. Arranged. By arranging the nozzles N in this manner, it is possible to reduce the substantial interval between the nozzles N projected in the longitudinal direction (X direction) of the inkjet head 122, and the nozzles N can be arranged at high density. In this case, the substantial arrangement direction of the nozzles N is the X direction. That is, the nozzle N is disposed substantially along the longitudinal direction of the inkjet head 122.

  Each head module 124-i is individually provided with an ink supply port (not shown), and ink is supplied individually.

[Control system of inkjet recording apparatus]
As shown in FIG. 25, the inkjet recording apparatus 100 includes a conveyance control unit 114, a recording control unit 132, a reading control unit 142, a drying control unit 162, a pass / fail distribution control unit 172, a paper discharge control unit 182 and a streak detection device 190. , An input unit 200, a system control unit 202, and the like.

  The conveyance control unit 114 controls the conveyance drum 110, the recording drum 112, and the chain gripper 150 to convey the paper P. The recording control unit 132 controls the ink jet head unit 120 (an example of a printing unit), discharges ink from the ink jet heads 122C, 122M, 122Y, and 122K onto the paper P, and records an image on the recording surface of the paper P.

  The reading control unit 142 controls the inline sensor 140 to read an image recorded on the recording surface of the paper P. The drying control unit 162 controls the heater 160 to dry the paper P conveyed by the chain gripper 150. The pass / fail distribution control unit 172 controls the stamper 170 to attach ink to the leading edge of the rejected paper P. The paper discharge control unit 182 controls the paper discharge stand 180 to keep the uppermost position of the stacked sheets P constant.

  As the streak detection device 190, any one of the streak detection devices 1 and 2 and the streak detection system 90 can be applied. Here, the image reading unit 16 is used as an input unit that acquires image data read by the inline sensor 140 as a read image.

  The input unit 200 is a user interface for a user to input print job information such as a print source image, the number of prints, a print application, and print conditions.

  Based on the print job input from the input unit 200, the system control unit 202 is based on the transport control unit 114, the recording control unit 132, the reading control unit 142, the drying control unit 162, the pass / fail distribution control unit 172, and the paper discharge control unit. By controlling 182 and the streak detecting device 190, the operation of the ink jet recording apparatus 100 is comprehensively controlled and a print job is executed.

  In the ink jet recording apparatus 100 configured as described above, the recording drum 112, the conveyance control unit 114, the ink jet head unit 120, and the recording control unit 132 include the streak detection devices 1 and 2 and the streak image output unit 70 of the streak detection system 90. It also functions as an example of printing means.

  According to the ink jet recording apparatus 100 configured as described above, a streak-added image in which streaks are intentionally added to a printing source image is printed on a print medium by the ink-jet head unit 120 and output as a printed matter. As a result, it is possible to obtain a determination result as to whether or not the image defect is acceptable as a printed matter, and set a streak detection condition from the determination result and the image feature amount at the streak position.

  Further, it is possible to detect a streak from a printed material of a printing source image printed by the inkjet head unit 120 based on the streak detection condition, and to determine whether the printed material is good or bad based on the detection result.

  Therefore, it is possible to set an optimal image defect detection condition according to the printing source image, and to appropriately determine whether or not the image is defective.

  Further, according to the inkjet recording apparatus 100, a chart image to which an image defect is added at a predetermined position and intensity is printed on a print medium by the inkjet head unit 120 and output as a printed matter. A determination result of whether or not the image defect is acceptable can be acquired, and a streak detection condition can be set based on the determination result and the image feature amount at the streak position.

  Furthermore, it is possible to detect a streak from a printed material of a printing source image printed by the inkjet head unit 120 based on the streak detection condition, and to determine whether the printed material is good or bad based on the detection result.

  Therefore, it is possible to set an optimal image defect detection condition according to the printing source image, and to appropriately determine whether or not the image is defective.

<Sixth Embodiment>
The position of the streak added by the streak-added image can be determined according to the characteristics of the ink jet recording apparatus 100 and the ink jet head 122.

  The inkjet recording apparatus 100 records an image by ejecting ink from the inkjet heads 122C, 122M, 122Y, and 122K, which are line heads, onto the paper P conveyed by the recording drum 112. For this reason, streaks generated in the ink jet recording apparatus 100 are generated in a direction along the conveyance direction of the paper P in the recording drum 112.

  In the ink jet recording apparatus 100, ejection abnormalities such as non-ejection and bending may occur due to causes such as ink thickening inside the nozzles N. Due to such an abnormal nozzle N, streaks are generated in the direction along the transport direction of the paper P.

  The ejection failure nozzle N can perform normal ejection by performing recovery processing such as forcibly ejecting ink. However, the nozzle N that has failed to discharge is more likely to cause a discharge abnormality again than other nozzles N that maintain a normal state even after returning from the discharge abnormality.

  Therefore, the system control unit 202 (an example of the printing element information acquisition unit) acquires information on the nozzles N that have caused ejection abnormalities in the past and stores the information in a memory (not shown), and based on the information in the memory. Then, a streak-added image is generated in which streaks are added to the positions of the nozzles N having a history of occurrence of ejection abnormality in the past with respect to the printing source image. By setting the streak determination condition using this streak added image, it is possible to set the streak determination condition according to the inkjet heads 122C, 122M, 122Y and 122K to be used.

  Further, as shown in FIGS. 22 and 23, the inkjet heads 122C, 122M, 122Y and 122K are configured by connecting a plurality of head modules 124-i (i = 1, 2,..., 16), respectively. Yes. Here, the connection characteristics of the head module 124-i (the end portion of the head module 124-i) are often inferior in discharge characteristics to the central portion of the head module 124-i due to the structure. For this reason, ejection abnormalities are likely to occur near the connection region of the head modules 124-i of the inkjet heads 122C, 122M, 122Y, and 122K, and as a result, there is a high probability that streaks will occur on the printed matter.

  Therefore, the system control unit 202 (an example of module information acquisition unit) acquires information on the plurality of head modules 124-i constituting the inkjet heads 122C, 122M, 122Y, and 122K, and nozzles in the connection region of the head modules 124-i. A streak-added image is generated in which streaks are added to the position (the connected position, the position of the nozzle at the end of the head module 124-i). By setting the streak determination condition using this streak added image, it is possible to set the streak determination condition according to the inkjet heads 122C, 122M, 122Y and 122K to be used.

  The technical scope of the present invention is not limited to the scope described in the above embodiment. The configurations and the like in the respective embodiments can be appropriately combined among the respective embodiments without departing from the spirit of the present invention.

  DESCRIPTION OF SYMBOLS 1, 2 ... Line detection apparatus, 10 ... Line detection part, 34 ... Line determination part, 40, 80 ... Detection condition setting part, 42 ... Print source image input part, 44 ... Line addition setting part, 46 ... Line addition image generation , 48... Image feature amount calculation unit, 50... Streak addition image determination input unit, 52 and 54... Streak setting unit, 60... Control unit, 70... Streak image output unit, 82. System, 94 ... detection condition setting server

Claims (14)

Image defect addition setting means for setting the position of the image defect intentionally added to the printing source image;
Image feature amount acquisition means for acquiring an image feature amount at a position to which the image defect of the printing source image is added;
Defect addition image generation means for generating a defect addition image in which the image defect is added to a position set by the image defect addition setting means of the original image;
A determination result acquisition means for acquiring a determination result as to whether or not the added image defect of the printed matter on which the defect-added image is printed by a print head is an image defect acceptable as a printed matter;
Detection condition setting means for setting an image defect detection condition from the image feature amount at the position where the image defect is added and the determination result;
An image defect detection apparatus comprising: The image defect addition setting means sets the strength of the image defect to be added,
The image defect detection apparatus according to claim 1, wherein the detection condition setting unit sets an image defect detection condition from the intensity of the added image defect.   3. The image defect detection device according to claim 1, further comprising an image defect detection unit configured to detect an image defect from a printed material on which the printing source image is printed by a print head based on the set detection condition.   The image defect detection apparatus according to claim 3, further comprising a determination unit configured to determine whether or not the printed material is good based on a detection result of the image defect detection unit. The print head is an inkjet head having a plurality of nozzles that eject ink;
A recording element information acquisition means for acquiring information of a plurality of nozzles constituting the inkjet head;
The said image defect addition setting means sets the position of the nozzle which has the log | history which generate | occur | produced the discharge abnormality in the past among these nozzles in the position of the said image defect to add. Image defect detection device. The print head is configured by connecting a plurality of modules,
The defect-added image is printed by the print head in a single pass method,
Module information acquisition means for acquiring information of a plurality of modules constituting the print head,
The image defect detection device according to claim 1, wherein the image defect addition setting unit sets a connection position of the plurality of modules to a position of the image defect to be added. Required quality level acquisition means for acquiring a quality level representing the degree of quality required for the printed matter;
Analyzing means for analyzing a visibility level representing a degree of visibility of an image defect at each position of the printing source image;
With
The image defect addition setting means sets the position of the first visibility level in the printing source image as the position of the added image defect when the required quality level is the first quality level. When the required quality level is a second quality level that is relatively lower than the first quality level, the visibility level of the printing source image is relative to the first visibility level. The image defect detection device according to any one of claims 1 to 6, wherein a position of a second visibility level that is higher than the first is set as the position of the image defect to be added.   The image defect detection device according to claim 1, wherein the image defect addition setting unit sets a position and a length of a stripe intentionally added to the printing source image. Determination result acquisition for acquiring a determination result as to whether or not the added image defect of the printed matter on which the chart image to which the image defect is added at a predetermined position and intensity is printed is an acceptable image defect as the printed matter Means,
Image feature amount acquisition means for acquiring an image feature amount at a position where the image defect of the chart image is added;
Detection condition setting means for setting the image defect detection condition from the intensity of the added image defect, the image feature amount at the position where the image defect is added, and the determination result;
An image defect detection apparatus comprising: Image defect addition setting means for setting the position of the image defect intentionally added to the printing source image;
Image feature amount acquisition means for acquiring an image feature amount at a position to which the image defect of the printing source image is added;
Defect addition image generation means for generating a defect addition image in which the image defect is added to a position set by the image defect addition setting means of the original image;
Printing means for printing the defect-added image on a print medium by a print head and outputting it as a printed matter;
A determination result acquisition means for acquiring a determination result as to whether or not the added image defect of the printed matter on which the defect addition image is printed is an image defect acceptable as a printed matter;
Detection condition setting means for setting an image defect detection condition from the image feature amount at the position where the image defect is added and the determination result;
With
The printing means prints the printing source image on a printing medium by a print head and outputs it as a printed matter,
Furthermore, based on the set detection condition, image defect detection means for detecting an image defect from a printed matter on which the printing source image is printed,
Determination means for determining pass / fail of a printed matter on which the printing source image is printed based on a detection result of the image defect detection means;
An image recording apparatus comprising: Printing means for printing a chart image to which an image defect is added at a predetermined position and intensity on a print medium by a print head and outputting the print image as a printed matter;
A determination result acquisition means for acquiring a determination result as to whether or not the added image defect of the printed matter on which the chart image is printed is an image defect acceptable as a printed matter;
Image feature amount acquisition means for acquiring an image feature amount at a position where the image defect of the chart image is added;
Detection condition setting means for setting the image defect detection condition from the intensity of the added image defect, the image feature amount at the position where the image defect is added, and the determination result;
With
The printing means prints a printing source image on a printing medium by a print head and outputs it as a printed matter,
Furthermore, based on the set detection condition, image defect detection means for detecting an image defect from a printed matter on which the printing source image is printed,
Determination means for determining pass / fail of a printed matter on which the printing source image is printed based on a detection result of the image defect detection means;
An image recording apparatus comprising: An image defect addition setting step for setting the position of an image defect intentionally added to the printing source image;
An image feature amount acquisition step of acquiring an image feature amount of a position to which the image defect of the printing source image is added;
A defect addition image generation step of generating a defect addition image in which the image defect is added to the position set in the image defect addition setting step of the printing source image;
A determination result acquisition step of acquiring a determination result as to whether or not the added image defect of the printed matter on which the defect-added image is printed by a print head is an image defect acceptable as a printed matter;
A detection condition setting step of setting an image defect detection condition from the image feature amount at the position where the image defect is added and the determination result;
An image defect detection method comprising: Determination result acquisition for acquiring a determination result as to whether or not the added image defect of the printed matter on which the chart image to which the image defect is added at a predetermined position and intensity is printed is an acceptable image defect as the printed matter Process,
An image feature amount acquisition step of acquiring an image feature amount at a position where the image defect of the chart image is added;
A detection condition setting step of setting a detection condition of the image defect from the intensity of the added image defect, the image feature amount of the position where the image defect is added, and the determination result;
An image defect detection method comprising:   A program for causing a computer to execute the steps of the image defect detection method according to claim 12 or 13.