JP2021071300A - Image inspection device and image inspection system - Google Patents

Abstract

To solve the problem in inspecting an image in which streak-like defects and noise cannot be separated.SOLUTION: An image inspection device 3 comprises: a change amount calculation unit 611 for calculating a classification result obtained by classifying the difference value calculated from a read image by a classification threshold into a first and a second classified value, as a change amount of a pixel value; a defect feature quantity extraction unit 612 for obtaining a first and a second count result for each sub-scan direction of the classification result, and extracting the value derived by adding up the number of first classification values included in the first count result and the number of second classification values included in the second count result separate by the second number of pixels in the main scan direction, as a plurality of feature quantities of streak-like defects occurring in an image formed on a recording material; and a quality determination unit 613 for comparing, for each of the same positions in the main scan direction, the value calculated from the plurality of feature quantities with a preset defect detection threshold to detect a streak-like defect, and determining the quality of the image formed on the recording material.SELECTED DRAWING: Figure 4

Description

The present invention relates to an image inspection device and an image inspection system.

When printing a large amount of prints, the operator usually performs trial printing several times to make various adjustments, and when it is confirmed by a sample that there is no problem in the printed contents, the main printing is started. However, in the image of the printed paper, color deviation or distortion may occur with respect to the sample for some reason. Therefore, in recent years, there has been provided an inspection system in which a scanning device such as a scanner is provided on a transport path in the subsequent stage of the image forming apparatus, and the image inspection device inspects the scanned image obtained by reading the image of each paper to be printed out. It became so. In this inspection, an image that is the source of the image formed on the paper is saved as an output target image. Then, the image inspection device compares the image (scanned image) obtained by scanning the paper printed by the main printing with a scanner and the stored output target image.

Comparing the scanned image with the output target image, image defects may be detected in the scanned image. Examples of the types of image defects include narrow streaks and bands that appear continuously in a predetermined direction or interrupted in a predetermined direction. Such image defects are collectively referred to as streak-like defects. However, in the following description, the streak-like defect is also abbreviated as "streak". A streak is a defect caused by scratches or stains on a drum or roller of a reading device such as an image forming device or a scanner, and is a gradation difference (also referred to as a brightness value) of a pixel value (also referred to as a brightness value) not intended by the operator. It also appears as "streak strength") or uneven density. Examples of the streaks include white streaks that are lighter than the original image, black streaks that are darker than the original image, and the like. Since streaks are likely to occur repeatedly and are easily recognized by operators and customers, it is required to reliably detect streaks even during the main printing.

A technique disclosed in Patent Document 1 is known for detecting streaks. In this Patent Document 1, a second difference image obtained by taking a difference from a pixel separated by a predetermined number of pixels from the first difference image between the output target image and the read image is generated, and the second difference image is generated. On the other hand, the number of the first pixel of the pixel whose pixel value is larger than the first threshold value and the number of the second pixel of the pixel whose pixel value is smaller than the first threshold value are calculated, and the second pixel number for each pixel string is calculated. A technique for determining a streak based on the ratio of the number of pixels of 1 to the number of pixels of 2 is disclosed.

Japanese Unexamined Patent Publication No. 2017-173000

The streaks appear in the sub-scanning direction or the main scanning direction of the image formed on the paper due to various factors. For example, when the band electrode included in the image forming apparatus is contaminated with toner or the like, the contaminated portion may not be charged well, and as a result, it may appear as a streak in the sub-scanning direction of the image. Further, when a defect occurs in a rotating body such as a photoconductor drum, streaks appear in the main scanning direction in synchronization with the rotation cycle of the rotating body.

FIG. 1 is a graph showing an example of data in which pixel values are averaged in the sub-scanning direction (FD: Feed direction). The horizontal axis of this graph represents the main scanning position of the scanned image in the main scanning direction (CD: Cross direction), and the vertical axis represents the pixel value for each pixel of the scanned image read in the G-ch (green channel). Represent. This graph is an average of the pixel values of the pixels in the sub-scanning direction at the same position in the main scanning direction based on the result of reading a flat image by a scanning device such as a scanner. In the following example, the printing direction in which images and characters are formed on the sheet will be described as matching the main scanning direction, but the same applies when the printing direction coincides with the sub-scanning direction. It is assumed that the scanned image shown in FIG. 1 has two streaks in the sub-scanning direction.

The streaks that occur continuously on the printed matter are easily noticeable and easy for the operator to see. However, the difference between the pixel values of the image is often very small between the place where there is a streak and the place where there is no streak. Therefore, even if the scanned image has streaks, the fluctuation of the pixel value averaged in the sub-scanning direction is almost the same as the fluctuation of the pixel value caused by the density unevenness at other positions where there is no streak. The technique disclosed in Patent Document 1 generates a second difference image in which a difference is obtained from pixels separated by a predetermined number of pixels in the first difference image, but a streak that can be visually recognized by an operator is generated. Could not be detected.

The present invention has been made in view of such a situation, and an object of the present invention is to enable detection of streak-like defects occurring in a scanned image.

In order to achieve at least one of the above-mentioned objects, an image inspection apparatus reflecting one aspect of the present invention is noted among a plurality of pixels included in a scanned image read from a recording material on which an image is formed. The difference value of the pixel value of the comparison pixel, which is separated by the number of the first pixels in the first direction with respect to the pixel value of the pixel with respect to the pixel of interest, is calculated, and the difference value is set to the first and second classification values by the classification threshold. The change amount calculation unit that calculates the classified classification result as the change amount of the pixel value, and the first that counts the same number of first classification values for each second direction that intersects with the first direction of the classification result. The number of the first classification value included in the first count result and the number of second pixels in the first direction are obtained by obtaining the count result of and the second count result obtained by counting the number of the second classification values. Feature quantity extraction that extracts the value obtained by adding the number of the second classification values included in the second count result, which are separated by a distance, as a plurality of feature quantities of streaky defects generated in the image formed on the recording material. A streak-like defect is detected by comparing a value calculated from a plurality of feature quantities with a preset defect detection threshold value at the same position in the first direction, and the image formed on the recording material. It is equipped with a quality judgment unit that judges quality.
The above-mentioned image inspection apparatus is one aspect of the present invention, and an image inspection system reflecting one aspect of the present invention is configured in the same manner as the above-mentioned image inspection apparatus.

According to the present invention, since the presence or absence of visible streak-like defects is accurately detected by utilizing the characteristics of the streaks, the quality of the image formed on the recording material can be improved.
Issues, configurations and effects other than those described above will be clarified by the following description of the embodiments.

It is a graph which shows an example of the data which averaged the pixel value in the sub-scanning direction. It is a schematic block diagram of the image inspection system which concerns on 1st Embodiment of this invention. It is a block diagram which shows the structural example of the control system of the image forming apparatus which concerns on 1st Embodiment of this invention. It is a block diagram which shows the structural example of the control system of the image inspection apparatus which concerns on 1st Embodiment of this invention. It is a figure which shows the example of the scanned image which concerns on 1st Embodiment of this invention. It is a figure which shows the example of the difference image which concerns on 1st Embodiment of this invention. It is a figure which shows the example of the classification result which concerns on 1st Embodiment of this invention. It is a figure which shows the state of the process which the defect feature amount extraction part which concerns on 1st Embodiment of this invention extracts a streak feature amount. It is a flowchart which shows the example of the processing performed by the inspection processing apparatus which concerns on 1st Embodiment of this invention. It is a figure which shows the appearance which the number of pixels of a specific pixel value included in the difference image which concerns on the modification of 1st Embodiment of this invention is counted in the vertical direction, and 1st and 2nd feature amount. It is a block diagram which shows the structural example of the control system of the image inspection apparatus which concerns on 2nd Embodiment of this invention. It is a graph which shows the example of the pixel value and the difference value of the pixel in the flat region and the non-flat region of the scanned image which concerns on 2nd Embodiment of this invention, and the classification threshold value. It is a flowchart which shows the example of the processing performed by the inspection processing apparatus which concerns on 2nd Embodiment of this invention.

Hereinafter, embodiments for carrying out the present invention will be described with reference to the accompanying drawings. In the present specification and the drawings, components having substantially the same function or configuration are designated by the same reference numerals, and redundant description will be omitted.

[First Embodiment]
<Configuration of image inspection system>
The present inventor has invented an image inspection device that detects streaks that can be visually recognized by an operator by taking a difference between a pixel of interest included in a scanned image and a comparison pixel near the pixel of interest. Hereinafter, a configuration example and an operation example of an image inspection system including an image inspection device capable of detecting streaks from a scanned image according to the first embodiment will be described with reference to FIGS. 2 to 9.

First, a configuration example of the image inspection system according to the first embodiment of the present invention will be described with reference to FIG.
FIG. 2 is a schematic configuration diagram of the image inspection system 1 according to the first embodiment of the present invention. Note that FIG. 2 shows elements considered necessary for the description of the present invention or related elements thereof, and the image inspection system of the present invention is not limited to the example shown in FIG.

The image inspection system 1 includes an image forming device 2 and an image inspection device 3. The image forming apparatus 2 is an example of an image forming apparatus that forms an image on paper by an electrophotographic method that forms an image using static electricity. The image forming apparatus 2 forms a color image on paper in a tandem format in which toner images of four colors of yellow (Y), magenta (M), cyan (C), and black (K) are superimposed, for example. A PC (Personal Computer) 6 (see FIG. 3 to be described later) operated by an operator is connected to the image forming apparatus 2 via a LAN (Local Area Network) (not shown). Then, a job is input from the PC 6 to the image forming apparatus 2 via the LAN. The image forming apparatus 2 performs various processes such as an image forming process according to the submitted job.

First, a configuration example of the image forming apparatus 2 will be described.
The image forming apparatus 2 includes an image input unit 11 and an operation display unit 13 having an automatic document feeder (ADF: Auto Document Feeder) 12. Further, the image forming apparatus 2 includes a printer unit 10 having a paper feed tray 20 and an image forming unit 30.

The image input unit 11 optically reads an image from the document on the platen of the ADF 12 and A / D-converts the read image to generate image data. The image input unit 11 can also read an image from the original on the platen glass.

The operation display unit 13 is composed of a display unit including a liquid crystal panel and the like, and an operation unit including a touch sensor and the like. The display unit and the operation unit are integrally formed as, for example, a touch panel. The operation display unit 13 generates an operation signal indicating the operation content from the operator input to the operation unit, and supplies the operation signal to the control unit 50 (see FIG. 3 to be described later). Further, the operation display unit 13 displays the operation content and setting information by the operator on the display unit based on the display signal supplied from the control unit 50. It is also possible to configure the operation unit with a mouse, tablet, or the like, and to configure it separately from the display unit.

The paper feed tray 20 is a container for accommodating the paper Sh on which the image is formed by the image forming unit 30. Papers having different paper types, basis weights, and the like are stored in the paper feed trays 20. Paper Sh is an example of a recording material. The image forming apparatus 2 can also form an image on a resin sheet which is an example of a recording material. In the present embodiment, an example in which two paper feed trays 20 are provided has been given, but the number of paper feed trays 20 may be one or three or more.

The image forming apparatus 2 is provided with a transport path 21 for transporting the paper Sh fed from the paper feed tray 20 to the image inspection device 3. The transport path 21 is provided with a plurality of transport rollers for transporting the paper Sh.

On the downstream side of the fixing portion 36, the transport path 21 extends and is connected to the transport path 41 of the image inspection device 3. Further, the transport path 21 branches on the downstream side of the fixing portion 36. An inverted transport path 22 that joins the transport path 21 on the upstream side of the printer unit 10 is connected to one end of the branched transport path 21. The reversing transfer path 22 is provided with a reversing portion 23 for reversing the paper Sh. The paper Sh flipped by the reversing section 23 is returned to the upstream side of the transport path 21 through the reverse transport path 22. Further, the paper Sh that has been inverted due to the route switching may be returned to the transport path 21 on the downstream side of the fixing portion 36 and then transported to the image inspection device 3.

The image forming unit 30 includes four image forming units 31Y, 31M, 31C and 31K for forming toner images of each color of Y, M, C and K, and forms an image on paper Sh. The image forming units 31Y, 31M, 31C and 31K have a charging unit, an exposure unit (all not shown), a photoconductor drum 32Y, 32M, 32C, 32K as an image carrier, and a developing unit 33Y, 33M, 33C, respectively. , 33K.

The developing units 33Y, 33M, 33C, and 33K irradiate the surfaces (outer peripheral portions) of the photoconductor drums 32Y, 32M, 32C, and 32K with light according to the image, thereby electrostatically irradiating the peripheral portions of the photosensitizing drums. Form a latent image. Then, the developing units 33Y, 33M, 33C, 33K form a toner image on the photoconductor drums 32Y, 32M, 32C, 32K by adhering the toner to the electrostatic latent image.

Further, the image forming unit 30 includes an intermediate transfer belt 34, a secondary transfer unit 35, and a fixing unit 36. The intermediate transfer belt 34 is a belt on which images formed on the photoconductor drums 32Y, 32M, 32C, and 32K are primarily transferred. The secondary transfer unit 35 is a roller that secondarily transfers the toner images of each color primary transferred onto the intermediate transfer belt 34 onto the paper Sh transported along the transport path 21.

The fixing unit 36 is arranged on the downstream side of the secondary transfer unit 35 in the paper transport direction, and performs a fixing process on the paper Sh on which the color toner image supplied from the image forming unit 30 is formed. The fixing unit 36 fixes the image transferred by the image forming unit 30 on the surface side of the paper Sh by heating and pressurizing the conveyed paper Sh. The paper Sh on which the image is fixed by the fixing section 36 is conveyed to the image inspection device 3 by the conveying path 21, or is conveyed on the upstream side of the printer section 10 after being inverted by the inversion section 23 through the inversion conveying path 22. Returned to Road 21. An image is formed on the back side of the paper Sh whose front and back sides are reversed by the printer unit 10. After that, the paper Sh that has been fixed by the fixing unit 36 is conveyed to the image inspection device 3.

Next, a configuration example of the image inspection device 3 will be described.
The image inspection device 3 performs an image inspection for detecting streaks generated in an image formed (printed) on the paper Sh conveyed from the image forming device 2. The processing of the image formed on the paper Sh, that is, the inspection of the image by the image inspection device 3, is mainly performed by the inspection processing device 5 attached to the image inspection device 3.

The image inspection device 3 is conveyed on the transfer paths 41, 42, 43, the switching unit 44, the reading units 45a, 45b, the colorimeter 46, and the transfer path 41 that convey the paper Sh conveyed from the image forming apparatus 2. It has paper ejection trays 47 and 48 from which the paper Sh is ejected.

The reading units 45a and 45b are examples of image input devices such as image sensors, respectively. The reading units 45a and 45b project light onto the surface of the paper Sh, for example, and capture the reflected light from the paper Sh as image data. The fact that the reading units 45a and 45b capture the image data of the paper Sh in this way is called "reading". The reading unit 45a reads the paper Sh transported through the transport path 41 from below the transport path 41, and the reading unit 45b reads the paper Sh conveyed through the transport path 41 from above the transport path 41. In the following description, since the reading units 45a and 45b are not distinguished, they are collectively referred to as "reading unit 45". Then, the reading unit 45 outputs the captured image data to the inspection processing device 5.

The colorimeter 46 reads an image formed on the upper surface of the paper Sh transported through the transport path 41, and measures the color density (reflection density) of the image based on the image information obtained by reading the image. This is an example of a device. The colorimeter 46 is, for example, a colorimeter capable of measuring the intensity (spectrum) of reflected light for each wavelength of light, and measures the measured color density (reflection density), L * a * b * value, and the like. Output. For the colorimeter 46, for example, a scanner (line sensor) in which a plurality of sensors (photoelectric conversion elements) (not shown) are arranged one-dimensionally over the entire area in the paper width direction (direction orthogonal to the paper transport direction) is used. To. When the colorimeter 46 is configured by a scanner, the image is read while moving the scanner in a direction orthogonal to the arrangement direction (paper transport direction). Then, the colorimeter 46 measures the color density of the image formed on the paper Sh for each region obtained by dividing the region where the image is read into a mesh shape. The colorimeter 46 outputs the measured color density information to the inspection processing device 5.

The colorimeter 46 may be composed of a single sensor, and the sensor may be moved two-dimensionally to measure the color density of the image formed on the paper Sh. Alternatively, the colorimeter 46 may be composed of a plurality of sensors arranged two-dimensionally (matrixally), and the plurality of sensors may read the color density of all pixels on the paper by one measurement.

The image inspection device 3 includes transport paths 42 and 43 connected to the transport path 41.
The transport path 42 is a path that branches from the middle of the transport path 41, and the paper Sh inspected by the inspection processing device 5 is discharged to the paper discharge tray 47 (an example of the paper discharge unit). Paper Sh (also referred to as “normal paper”) whose image is determined to be normal by the inspection processing device 5 is discharged to the paper ejection tray 47.

The transport path 43 is also a path that branches from the middle of the transport path 41, and the paper Sh inspected by the inspection processing device 5 is discharged to the paper discharge tray 48 (an example of the paper discharge portion). Paper Sh (also referred to as “abnormal paper”) whose image is determined to be abnormal by the inspection processing device 5 is discharged to the paper ejection tray 48.

The switching unit 44 switches the transport direction of the paper Sh so that the paper Sh is transported to either the transport path 42 or 43. If the image inspection device 3 has only one paper ejection tray 47, normal paper and abnormal paper are mixed and ejected. In this case, the normal paper and the abnormal paper are discharged, for example, with a slight shift in the direction orthogonal to the discharge direction.

The paper Sh conveyed to the image inspection device 3 is a printed matter having an image formed on both sides or one side. The image inspection device 3 reads the image formed on both sides or one side of the paper Sh by the image forming device 2, and the inspection processing device 5 performs a predetermined inspection.

In this embodiment, since the image forming apparatus 2 can form an image on both sides of the paper Sh, the inspection processing apparatus 5 inspects both sides of the paper Sh. However, the inspection processing device 5 may be configured to inspect only one side of the paper Sh conveyed from the image forming apparatus capable of forming an image on only one side of the paper Sh.

[Structure of control system of image forming apparatus]
Next, a configuration example of the control system of the image forming apparatus 2 will be described with reference to FIG.
FIG. 3 is a block diagram showing a configuration example of the control system of the image forming apparatus 2.
The image forming apparatus 2 mainly includes a communication I / F unit 51, a paper conveying unit 24, an image input unit 11, an image forming unit 30, a control unit 50, a storage unit 52, a fixing unit 36, and an operation display unit 13. Be prepared.

The communication I / F unit 51 is an interface for transmitting and receiving data to and from a PC 6 which is a terminal operated by an operator via a network or a dedicated line. As the communication I / F unit 51, for example, a NIC (Network Interface Card) is used.

The paper transport unit 24 drives a transport path 21 shown in FIG. 2, a transport roller (not shown) provided on the reverse transport path 22, and a reverse section 23 based on control by the control unit 50.

The control unit 50 includes a CPU (Central Processing Unit) 501, a ROM (Read Only Memory) 502, a RAM (Random Access Memory) 503, and an input image processing unit 504.
The ROM 502 stores a program executed by the CPU 501 of the control unit 50, data used when executing the program, and the like. The CPU 501 controls each part constituting the image forming apparatus 2 by reading the program stored in the ROM 502.
Variables and parameters generated during the arithmetic processing of the CPU 501 are temporarily written in the RAM 503.

The input image processing unit 504 performs predetermined image processing (for example, rasterization processing) on the input image included in the job input from the PC 6 via the communication I / F unit 51 to create print image data. Further, the input image processing unit 504 also performs image processing on the image data acquired from the document read by the image input unit 11 by the ADF 12 or the image data acquired from the outside to create image data for printing. The image data for printing is sent to the image forming unit 30 and the image inspection device 3. In the image inspection apparatus 3, the image data for printing is stored as an output target image 603b (see FIG. 4 described later).

The control unit 50 controls the paper transport unit 24 to drive the transport roller to transport the paper Sh on the transport path 21. Further, the control unit 50 outputs the print image data created by the input image processing unit 504 to the image forming unit 30. Further, the control unit 50 controls the image forming unit 30 to form an image on the paper Sh. Further, the control unit 50 controls the fixing unit 36 to fix the image on the paper Sh.

Further, the control unit 50 receives an operation signal from the operation display unit 13 and performs control according to the operation signal. Further, the control unit 50 outputs a display signal to the operation display unit 13, and the operation display unit 13 displays an operation screen for displaying various setting screens for inputting various operation instructions and setting information, various processing results, and the like. Display on the panel. The information displayed on the operation display unit 13 also includes the streak detection result 631 (see FIG. 4 described later) output from the image inspection device 3.

The storage unit 52 stores parameters used when the CPU 501 of the control unit 50 executes the program, data obtained by executing the program, and the like. For example, the storage unit 52 stores information such as image formation conditions for each density level. The storage unit 52 may store the program executed by the CPU 501.

[Configuration of control system for image inspection equipment]
Next, a configuration example of the control system of the image inspection device 3 will be described with reference to FIG.
FIG. 4 is a block diagram showing a configuration example of the control system of the image inspection device 3.

The image inspection device 3 includes a communication I / F unit 61, a paper transport unit 62, a reading unit 45, and a colorimeter 46 as main configurations. Further, the inspection processing device 5 attached to the image inspection device 3 includes a control unit 60 and a storage unit 63. Further, a storage device 4 is attached to the inspection processing device 5.

The communication I / F unit 61 is an interface for transmitting and receiving data to and from the image forming apparatus 2 via a network. For example, NIC is used as the communication I / F unit 61.
The paper transport unit 62 drives a transport roller (not shown) provided on the transport path 41 shown in FIG. 2 based on the control by the control unit 60.

As described above, the reading unit 45 reads the images formed on the upper surface and the lower surface of the paper Sh transported through the transport path 41. In the present embodiment, the image data of the paper Sh read by the reading units 45a and 45b is referred to as a "read image".

The image read by the reading unit 45 from the paper Sh on which the image is formed is stored in the RAM 603 of the control unit 60 as the read image 603a. Further, the RIP-processed print image data received by the inspection processing device 5 from the image forming device 2 is stored in the RAM 603 as an output target image 603b. As will be described in the second embodiment described later, the output target image 603b may also be used for inspecting the read image 603a. The scanned image 603a and the output target image 603b may be stored in a storage unit 63 composed of a large-capacity HDD or the like. Further, the color density information output from the colorimeter 46 to the image inspection device 3 may be included in the scanned image 603a and the output target image 603b.

The control unit 60 includes a CPU 601 and a ROM 602, a RAM 603, a change amount calculation unit 611, a defect feature amount extraction unit 612, and a quality determination unit 613.

The CPU 601 controls each part constituting the image inspection device 3 by reading the program stored in the ROM 602. By executing the program read from the ROM 602 by the CPU 601, the functions of the change amount calculation unit 611, the defect feature amount extraction unit 612, and the quality determination unit 613 are realized.

The ROM 602 stores a program executed by the CPU 601 of the control unit 60, data used when executing the program, and the like. The ROM 602 is used as an example of a computer-readable, non-transient recording medium that stores a program executed by the CPU 601.

Variables and parameters generated during the arithmetic processing of the CPU 601 are temporarily written in the RAM 603. As described above, the read image 603a, the output target image 603b, the difference image 603c1, the classification result 603d, and the parameter 603e are also stored in the RAM 603.

The parameter 603e includes various values set by the control unit 60 or the operator. The parameter 603e includes, for example, a defect detection threshold value for detecting a streak from a streak feature amount described later. The change amount calculation unit 611, the defect feature amount extraction unit 612, and the quality determination unit 613 perform various processes based on various values read from the parameter 603e.

The change amount calculation unit 611 is a difference between the pixel values of the pixels of interest among the plurality of pixels included in the scanned image 603a and the pixel values of the comparison pixels separated by the number of first pixels in the first direction with respect to the pixels of interest. The value is calculated, and the classification result 603d in which the difference value is classified into the first and second classification values by the classification threshold is calculated as the amount of change in the pixel value. Hereinafter, the first direction will be described as the main scanning direction, and the second direction will be described as the sub-scanning direction. However, if the direction of the streaks to be detected is the main scanning direction, the first direction may be the sub-scanning direction and the second direction may be the main scanning direction. That is, the first direction is either a horizontal direction parallel to the printing direction or a vertical direction perpendicular to the printing direction. Further, in the present embodiment, the number of first pixels is set to "3".

For example, the change amount calculation unit 611 calculates the difference value between the pixel value of the pixel of interest selected from the plurality of pixels included in the scanned image 603a and the pixel value of the comparison pixel. Then, the change amount calculation unit 611 generates a difference image 603c1 including the difference value calculated by performing the same processing on the other pixels of the read image 603a. At this time, the change amount calculation unit 611 takes a difference between the shift image (not shown) obtained by shifting the read image 603a in the horizontal or vertical direction by a predetermined number of pixels and the read image 603a before the shift, and obtains a difference image. It is possible to generate 603c1. The shift represents the distance between pixels for determining the comparison pixel with respect to the pixel of interest. Details of the difference image 603c1 will be described later with reference to FIG.

Further, the change amount calculation unit 611 generates a classification result 603d classified into a plurality of pixels for each pixel as a change amount based on the size and code of the difference value of each pixel included in the difference image 603c1. As described above, the classification result 603d is represented as a result of the change amount calculation unit 611 classifying (trivalentizing) the difference value by the classification threshold value for each of a plurality of pixels included in the difference image 603c1. The classification threshold is a value set in the parameter 603e.

In the present embodiment, the process in which the change amount calculation unit 611 refers to the classification threshold value and digitizes the difference value of each pixel included in the difference image 603c1 for each pixel is referred to as “multi-valued”. Depending on the classification threshold value, the change amount calculation unit 611 may multi-value the difference value of the difference image 603c1 to binarize, quaternize, or the like. Further, the classification threshold value is a value set in advance before the start of the image inspection, and may be set to a different value depending on the resolution of the scanned image 603a, the type of the image formed on the paper Sh, and the like. Details of the classification result 603d will be described with reference to FIG. 7, which will be described later.

The defect feature amount extraction unit 612 is a feature amount of streak-like defects generated in an image formed on the paper Sh based on a change amount calculated based on a plurality of pixels in the sub-scanning direction (“streak feature amount”). Is called) is extracted. For example, when the direction in which the streaks are generated is the sub-scanning direction, the defect feature amount extraction unit 612 refers to the classification result 603d for each predetermined position in the main scanning direction in the sub-scanning direction, and refers to the averaging result (three values). Extract the streak features from the averaging result). The ternary averaging result is a result obtained by the defect feature amount extraction unit 612 averaging the difference values classified by the classification threshold value by the change amount calculation unit 611 and multi-valued. It is shown in a graph represented by the ternary average value shown. The details of the streak feature amount will be described with reference to FIG. 8 described later.

Then, the defect feature amount extraction unit 612 refers to the classification result 603d in the sub-scanning direction for each predetermined position in the main scanning direction, and obtains a count result by counting the number of pixels for each classification of the classification result 603d (described later). See FIG. 10). When the direction in which the streaks are generated is the sub-scanning direction, the defect feature amount extraction unit 612 is a count result obtained at a position separated from the pixel of interest by the number of first pixels in the direction opposite to the direction in which the comparison pixel is located. The feature amount can be extracted by referring to.

The quality determination unit 613 detects streak-like defects by comparing a value calculated from a plurality of streak feature amounts with a preset defect detection threshold value at the same position in the main scanning direction, and forms streaks on the paper Sh. Judge the quality of the image. At this time, the quality determination unit 613 detects the streak-like defect based on the ratio of the count result at the predetermined position of the pixel of interest in the main scanning direction and the count result referred to at a position away from the pixel of interest (described later). See FIG. 10).

If the quality determination unit 613 does not detect a streak from the streak feature amount, the quality determination unit 613 determines that the read image 603a is normal. On the other hand, if the quality determination unit 613 detects a streak from the streak feature amount, the quality determination unit 613 determines that the read image 603a is abnormal. Then, the quality determination unit 613 stores the streak detection result 631 including the page number of the page that is the source of the read image 603a in the storage unit 63.

The streak detection result 631 is not only stored in the storage unit 63, but also sent to an external storage device 4 connected to the image inspection device 3. The storage device 4 may be, for example, a USB (Universal Serial Bus) memory, an SSD (Solid State Drive), an HDD (Hard Disk Drive), or the like connected to the image inspection device 3. By sending the streak detection result 631 to the storage device 4, the operator can display the streak detection result 631 stored in the storage device 4 and confirm the contents. The streak detection result 631 may be transferred and saved to a cloud server (not shown) or PC6 connected via the communication I / F unit 61.

Further, the control unit 60 transmits the streak detection result 631 read from the storage unit 63 as necessary to the image forming apparatus 2 or the PC 6 via the communication I / F unit 61. The image forming apparatus 2 can display the streak detection result 631 on the operation display unit 13. Therefore, the operators of the image forming apparatus 2 and the image inspection apparatus 3 can confirm the contents of the streak detection result 631 from the operation display unit 13. The operator can also confirm the content of the streak detection result 631 from the PC 6.

The control unit 60 selects a paper ejection tray (an example of a paper ejection destination) of the paper Sh to be conveyed along the conveying path 41 according to the streak detection result 631. For example, the control unit 60 operates the switching unit 44 to eject the normal paper conveyed to the transport path 42 to the output tray 47, and eject the abnormal paper conveyed to the transport path 43 to the output tray 48. Make it paper.

Further, the control unit 60 performs a page reprinting process (referred to as “recovery processing”) corresponding to the scanned image 603a written in the streak detection result 631 as having streaks through the communication I / F unit 61 to perform the image forming apparatus 2 Can be instructed to. The recovery process is performed automatically by the image inspection system 1 or manually by the operator after the rotating body that has caused the streaks has been cleaned or replaced by the operator.

Next, examples of scanned image, image shift, difference image, classification result, and streak detection will be described in order.
FIG. 5 is a diagram showing an example of the scanned image 603a. The scanned image 603a shows the pixel values of any of the channels R, G, and B for each pixel represented by one square in the figure.

The pixel value takes a number between "0" and "255" for each of the R, G, and B channels. In the figure, an example of a pixel of interest and a comparison pixel is shown. The comparison pixel is a pixel at a position shifted by one pixel number (for example, three pixels) in the horizontal direction when viewed from the pixel of interest. The comparison pixel may be a pixel at a position shifted by one pixel in the horizontal direction when viewed from the pixel of interest. The relationship between the pixel of interest and the comparison pixel also holds for other pixels.

The change amount calculation unit 611 obtains a difference value by subtracting the pixel value of the comparison pixel from the pixel value of the pixel of interest.
FIG. 6 is a diagram showing an example of the difference image 603c1.

As described above, the difference image 603c1 generated by the change amount calculation unit 611 stores the difference value between the attention pixel and the comparison pixel at the position of the attention pixel. For example, since the pixel value of the pixel of interest of the scanned image 603a shown in FIG. 5 is “79” and the pixel value of the comparison pixel is “90”, the difference value is “-11” (= 79-90). .. Such a calculation is also performed on the other pixels included in the scanned image 603a, and the difference image 603c1 is generated.

As described above, the difference image 603c1 stores the difference value for each pixel of interest. However, if the difference value is left as it is, the difference between the portion where the scanned image 603a has streaks and the portion where there is no streak is small, so that it is difficult to detect the streaks. Therefore, two threshold values are set in the parameter 603e, and the change amount calculation unit 611 uses the two threshold values to perform ternation processing for obtaining the classification result 603d in which the difference value of each pixel is classified into three types. ..
FIG. 7 is a diagram showing an example of the classification result 603d.

In the present embodiment, the parameter 603e is set to "+8" as the first classification threshold value and "-8" as the second classification threshold value. The change amount calculation unit 611 replaces the difference value of the pixel whose difference value is larger than the first classification threshold value with "255", and replaces the difference value of the pixel whose difference value is smaller than the second classification threshold value with "0". Further, the change amount calculation unit 611 replaces the difference value of the pixels whose difference value is equal to or more than the second classification threshold value and equal to or less than the first classification threshold value with “128”. From FIG. 7, it is shown that the difference value of each pixel included in the difference image 603c1 is replaced with any of "0", "128", and "255".

The first classification threshold value and the second classification threshold value are adjusted based on the density of streaks (gradation difference of pixel values) to be detected by the quality determination unit 613. For example, in a region without streaks, it is preferable to set a threshold value such that the difference value of most pixels is replaced with "128".

Here, the extraction process of the streak feature amount will be described with reference to FIG.
FIG. 8 is a diagram showing a state of processing in which the defect feature amount extraction unit 612 extracts the streak feature amount.

In the upper part of FIG. 8, the area of the flat image (referred to as “flat area”) known in advance in the scanned image 603a is sub-scanned at each specific position indicated by the main scanning position. A graph of the averaging results averaged in the direction is shown.
From the graph showing the result of averaging the pixel values, it is shown that there is a streak at the position where the main scanning position is “14”. It can be seen that the pixel value at the position where there is a streak has a little large fluctuation as compared with the peripheral pixel value. However, it is not clear whether this fluctuation was caused by noise or streaks.

A graph of the averaging result is shown in the middle of FIG.
The defect feature amount extraction unit 612 refers to the classification result 603d in the sub-scanning direction and averages the values of each pixel. By this processing, the defect feature amount extraction unit 612 averages the value (ternified value) of each pixel of the classification result 603d in the sub-scanning direction, and the ternary averaging value is represented by a graph. Get results. If there is no noise in the scanned image 603a, the ternary average value is 128. In the figure, the main scanning position indicated by the broken line circle is “10”, and the position of “14” is a position having a large difference from “128”. However, since the ternary average values at these positions have a small difference from the ternary average values in the periphery, it is difficult to detect them as streaks and separate them from noise.

Therefore, the defect feature amount extraction unit 612 extracts the streak feature amount from the ternation averaging result.
The lower part of FIG. 8 shows a graph of the streak feature amount calculated by the defect feature amount extraction unit 612.
Based on the ternary averaging result, the defect feature amount extraction unit 612 has a ternary averaging value of a certain main scanning position and a ternary value of the main scanning position that differs by 3 pixels in the horizontal direction from the main scanning position. The absolute value of the difference value is calculated by taking the difference from the average value.

The quality determination unit 613 is set to detect as a streak if the streak feature amount is "40" or more of the defect detection threshold value (value shown by the broken line in the figure) read from the parameter 603e. Then, the quality determination unit 613 determines that there is a large value at the position where the main scanning position is “14”. In this case, the quality determination unit 613 can detect the streaks at the position where the main scanning position is “14”. Then, the quality determination unit 613 determines that the image formed on the paper Sh is abnormal.

Next, an example of the processing performed by the inspection processing apparatus 5 will be described with reference to FIG.
FIG. 9 is a flowchart showing an example of processing performed by the inspection processing apparatus 5 according to the first embodiment.

First, the change amount calculation unit 611 shifts the read image 603a (for example, FIG. 5) read from the RAM 603 and inputs the image by the number of first pixels (for example, 3 pixels) (S1). Then, the change amount calculation unit 611 generates a difference image 603c1 (for example, FIG. 6) based on the shift image obtained in step S1 and the read image 603a that has not been processed in step S1 (S2).

Next, the change amount calculation unit 611 performs ternation processing of the difference image 603c1 based on the first classification threshold value and the second classification threshold value read from the parameter 603e, and classifies each pixel including the ternary value. The result 603d (eg, FIG. 7) is generated (S3).

Next, the defect feature amount extraction unit 612 extracts the streak feature amount (for example, the lower part of FIG. 8) based on the classification result 603d (S4). Then, the quality determination unit 613 compares the extracted streak feature amount with the defect detection threshold value read from the parameter 603e, detects the streak (S5), and determines the quality of the read image 603a. The quality determination unit 613 writes the streak detection result 631 in the storage unit 63. After that, the inspection processing device 5 ends the main processing.

In the inspection processing apparatus 5 according to the first embodiment described above, the difference image 603c1 is obtained by taking the difference between the shift image obtained by shifting the read image 603a by several pixels and the read image 603a, and then obtaining the difference image 603c1. The streaks in the read image 603a are detected by ternating the difference image 603c1 and extracting the streak feature amount. In the inspection processing device 5, even if the region where the streaks are generated in the scanned image 603a is flat, the inspection processing device 5 can detect the streaks, so that the streak detection accuracy is improved.

[Modified example of the first embodiment]
Although FIG. 8 shows an example of averaging the classification results, the defect feature amount extraction unit 612 may detect streaks based on the ratio of counting the classification values. Here, the processing of the defect feature amount extraction unit 612 and the quality judgment unit 613 according to this modification will be described.

The defect feature amount extraction unit 612 counts the number of the same first classification values for each sub-scanning direction that intersects the main scanning direction of the classification result 603d, and the number of the first counting results and the number of the second classification values. The second count result included in the second count result is separated from the number of the first classification values included in the first count result by the number of second pixels in the main scanning direction. The value obtained by adding the number of the classification values of 2 is extracted as a plurality of feature quantities of the streak-like defects generated in the image formed on the recording material.

Then, the quality determination unit 613 detects the streak-like defect by comparing the value calculated from the plurality of feature quantities with the preset defect detection threshold along the main scanning direction, and is formed on the recording material. Judge the quality of the image. At this time, the quality determination unit 613 detects streak-like defects as a plurality of feature quantities when the ratio of the first feature quantity and the second feature quantity at the same position in the main scanning direction is equal to or greater than the defect detection threshold value. To do.

A specific method for detecting streaky defects will be described with reference to FIG.
FIG. 10 is a diagram showing a state in which the number of pixels of a specific pixel value included in the difference image 603c1 is counted in the vertical direction, and the first and second feature amounts.

As shown on the upper side of FIG. 10, the defect feature amount extraction unit 612 obtains the first and second count results. In the figure, "+8" represents the first classification threshold value described with reference to FIG. 7, and "-8" represents the second classification threshold value. Then, in FIG. 10, the defect feature amount extraction unit 612 counts the number of pixels including pixel values larger than “+8” in the sub-scanning direction of the difference image 603c1, and the first count result and the sub of the difference image 603c1. The second count result of counting the number of pixels including the pixel value smaller than "-8" in the scanning direction is shown.

That is, in the first and second count results, the defect feature amount extraction unit 612 sets the number of classification values included in the classification result 603d in the sub-scanning direction for each classification value (for example, "0" and "255"). ) Can be said to be the value counted. Therefore, the defect feature amount extraction unit 612 has the first count result of counting the number of pixels including the classification value larger than, for example, "200" with respect to the classification value of the pixels included in the classification result 603d, and the difference image. A second count result obtained by counting the number of pixels including a classification value smaller than "100" in the sub-scanning direction of 603c1 may be obtained.

FIG. 10 shows how the first and second count results are arranged so that the main scanning positions match. Then, the defect feature amount extraction unit 612 adds the counted results to the counted results in the comparison pixel sequence separated by 3 pixels (an example of the number of second pixels) in the horizontal direction. At this time, the defect feature amount extraction unit 612 has the first count result at the position of the pixel 71 of the attention pixel row in the main scanning direction of the classification result 603d and the second number of pixels from the position of the pixel 71 of the attention pixel row (for example,). A value obtained by adding the second count result, which is separated by 3 pixels), is extracted as the first feature amount. Further, the defect feature amount extraction unit 612 is separated from the second count result at the position of the pixel 72 of the attention pixel row of the main scan of the classification result 603d by the number of second pixels from the position of the pixel 72 of the attention pixel row. The value obtained by adding the first count result and the first count result is extracted as the second feature amount.

The total value of the results counted by the defect feature amount extraction unit 612 is represented as the first feature amount and the second feature amount shown on the lower side of FIG. The first feature amount is a value obtained by adding the count results of pixels smaller than "-8" in the pixel sequence of interest and the count results of pixels larger than "+8" in the comparative pixel sequence. For example, the value "18" (first feature amount), which is the sum of the count result "9" of the pixel 72 of the pixel string of interest and the count result "9" of the pixel 81 of the comparison pixel row, is the pixel 91 of the first feature amount. Stored in.

The second feature amount is a total value of the count result of the pixel larger than "+8" of the pixel string of interest and the count result of the pixel smaller than "-8" of the comparison pixel string. For example, the value "1" (second feature amount), which is the sum of the count result "1" of the pixel 71 of the pixel string of interest and the count result "0" of the pixel 82 of the comparison pixel string, is the pixel 92 of the second feature amount. Stored in.

Then, the quality determination unit 613 calculates the ratio of the first feature amount and the second feature amount for each same pixel string. When this ratio is 10 times or more, the quality determination unit 613 detects streaks at the main scanning position of the pixel sequence of interest. In FIG. 10, since the ratio of 18/1 = 18 (times) is calculated, streaks are detected in the pixel sequence of interest. The threshold value of the ratio used for detecting the streaks is stored in the parameter 603e and can be appropriately changed by the operator.

Further, if the first classification threshold value and the second classification threshold value shown in FIG. 7 are adjusted according to the density of the streaks required to be detected, the quality determination unit 613 will perform the first classification for each of the same pixel strings. The streaks may be detected from the first feature amount or the second feature amount without calculating the ratio between the feature amount and the second feature amount.

It should be noted that the wide streaks have a gentle effect (change in pixel value) due to the streaks. Therefore, if the positions of the pixels to be extracted as the comparison pixels are too close to the pixels of interest, the difference from the comparison pixels becomes small and the streaks cannot be detected. On the other hand, if the comparison pixel is too far from the pixel of interest, the streaks generated in the narrow flat region cannot be detected.

Therefore, the number of first pixels calculated by the change amount calculation unit 611 in order to obtain the difference image 603c1 may be a plurality of different values (for example, 3 pixels, 5 pixels, 7 pixels, 15 pixels). Then, the change amount calculation unit 611 may generate a plurality of difference images 603c1 in which the difference values calculated for each of a plurality of different values are stored at the positions of the pixels of interest. By setting a plurality of shifts of the comparison pixel shifted by the change amount calculation unit 611 with respect to the attention pixel in the parameter 603e and obtaining the difference between the shift amount of one attention pixel and the comparison pixel shifted by a different shift number. , The presence or absence of streaks may be analyzed in parallel. By such a process, the defect feature amount extraction unit 612 may extract the streak feature amount from each of the plurality of difference images 603c1, and the quality determination unit 613 may detect the streak feature amount from the extracted streak feature amount. Thereby, the streaks appearing in the scanned image 603a can be detected regardless of the thickness of the streaks.

[Second Embodiment]
<Detection of streaks appearing in areas other than the flat image area>
In the above-described embodiment, an example of the process of detecting the streaks appearing in the flat region in the scanned image 603a has been described. If it is a flat region, the classification threshold value may be changed according to the density of the streaks to be detected (gradation difference of pixel values). Therefore, the change amount calculation unit 611 extracts only the flat region from the read image 603a to generate the difference image 603c1, the defect feature amount extraction unit 612 extracts the streak feature amount, and the quality determination unit 613 is extracted. It is sufficient to detect the streaks only in the area.

However, in an actual printed matter, not only a flat region but also a non-flat image region (referred to as "non-flat region") appears. For example, a streak on a non-flat region where there is a gradation in which the amount of fluctuation of the pixel value is small becomes conspicuous. Therefore, in the second embodiment, the process of detecting the streaks appearing in the non-flat region by the inspection processing device 5A will be described.

FIG. 11 is a block diagram showing a configuration example of the control system of the image inspection device 3. In the inspection processing device 5A included in the image inspection device 3 according to the present embodiment, when the RIP image used for forming an image on the paper Sh is sent from the image forming device 2 to the inspection device 3A, the printed matter is printed from the RIP image. The fluctuation amount of the pixel value in the non-flat region of is extracted, and the threshold value for ternation is changed based on the extracted fluctuation amount.

The control unit 60 of the inspection processing device 5A has an image conversion unit 615 and an alignment unit 616 in addition to the change amount calculation unit 611, the defect feature amount extraction unit 612, and the quality judgment unit 613 according to the first embodiment described above. To be equipped. Also in this embodiment, the functions of the image conversion unit 615 and the alignment unit 616 are realized by executing the program read from the ROM 602 by the CPU 601.

The output target image 603b stored in the RAM 603 is a bitmap format image that has been previously subjected to rasterization processing (RIP processing) by the control unit 50 of the image forming apparatus 2. The output target image 603b is the source of the image formed on the paper Sh by the image forming apparatus 2. An image determined in advance by the operator to be correct and read in advance by the reading unit 45 may be used as the output target image 603b.

Since the output target image 603b is used by the image forming apparatus 2 to form an image on the paper Sh, the CMYK color mode is set. Therefore, the image conversion unit 615 performs image conversion that matches the color mode of the output target image 603b with the color mode of the scanned image 603a. Here, the color mode of the scanned image 603a is RGB. Therefore, the image conversion unit 615 converts the color mode of the output target image 603b from CMYK to RGB. In the following description, the output target image 603b will be described assuming that the color mode has been converted to RGB.

The alignment unit 616 aligns the print position of the output target image 603b with the scanned image 603a read from the paper Sh on which the image is formed (referred to as "alignment"). At this time, the alignment unit 616 aligns the read image 603a read from the RAM 603 with the position of the output target image 603b stored in advance in the RAM 603.

Then, the change amount calculation unit 611 generates the difference image 603c2 by taking the difference between the read image 603a aligned by the alignment unit 616 and the output target image 603b. The difference image 603c2 is stored in the RAM 603 together with the difference image 603c1 obtained by taking the difference between the shift image of the read image 603a and the read image 603a before the shift described in the first embodiment.

Further, the change amount calculation unit 611 generates a threshold image 603f to be referred to for creating the classification result 603d based on the difference image 603c2. At this time, the change amount calculation unit 611 changes the classification threshold value according to the change in the pixel value of the read image 603a aligned by the alignment unit 616. The threshold image 603f is two types of images defined by the first classification threshold A and the second classification threshold B shown in FIG. 12, which will be described later, and is stored in the RAM 603. The change amount calculation unit 611 digitizes the difference image 603c1 based on the generated threshold image 603f, and obtains the classification result 603d.

FIG. 12 is a graph showing an example of pixel values, difference values, and classification thresholds of pixels in the flat region and the non-flat region of the scanned image 603a. The horizontal axis of this graph represents the main scanning position, and the vertical axis represents three types of values (pixel value, difference value, and classification threshold value). Further, the flat region and the non-flat region are defined by the graph of the difference value on the upper side of FIG.

The graph on the lower side of FIG. 12 shows the fluctuation of the pixel value of the output target image 603b subjected to the RIP processing. Further, in the graph on the upper side of FIG. 12, in the graph on the lower side of FIG. 12, as in FIG. 5, the pixel of interest and the pixel of interest are shifted by 3 pixels in the horizontal direction (direction orthogonal to the streak to be detected). It represents the variation of the difference value of the difference image 603c2 obtained by taking the difference from the comparison pixel. In the figure, the first classification threshold value A and the second classification threshold value B are described as “threshold value A” and “threshold value B”, respectively.

The pixel value of the output target image 603b is represented by a graph of a polygonal line L1. From the graph of the polygonal line L1, it is shown that the pixel value and the difference value do not change because the flat region is between “1” and “7” of the main scanning position. On the other hand, since the area from "7" to "33" of the main scanning position is a non-flat region, the pixel value and the difference value change. For example, the pixel value in the non-flat region gradually increases from "11" to "21" of the main scanning position and keeps a constant value, and then gradually decreases from "23" to "33" to the original value. Return to "128".

For example, the difference value is represented by a graph of a polygonal line L10. As shown in the graph of the polygonal line L10, the difference value in the non-flat region gradually decreases from "7" to "9" at the main scanning position, takes a constant negative value from "9" to "17", and becomes " It gradually increases from 17 "to" 23 ". Then, it takes a constant positive value from "23" to "30" of the main scanning position, gradually decreases from "30" to "33", and returns to the original value "0".

Here, a value obtained by adding a predetermined value (for example, "8") to the difference value is called a first classification threshold value A, and a value obtained by subtracting a predetermined value (for example, "8") from the difference value is called. , Called the second classification threshold B. The first classification threshold value A is represented by the graph of the polygonal line L11, and the second classification threshold value B is represented by the graph of the polygonal line L12.

In the following description, when the first classification threshold value A and the second classification threshold value B are not distinguished, they are collectively referred to as “classification threshold value”. The classification threshold is stored in parameter 603e. The classification thresholds are all referred to by the change amount calculation unit 611 for ternating the pixels specified by the main scanning position of the scanned image 603a.

FIG. 13 is a flowchart showing an example of processing performed by the inspection processing device 5A according to the second embodiment. In this process, the processes of steps S11 and S12 are the same as the processes of steps S1 and S2 of FIG. Therefore, after explaining the processing after step S21, the processing after step S13 will be described.

First, the image conversion unit 615 converts the color mode of the output target image 603b read from the RAM 603 from CMYK to RGB (S21). By this process, the image conversion unit 615 matches the color mode of the output target image 603b (RIP image) received from the image forming device 2 by the image inspection device 3 with the color mode of the scanned image 603a.

Next, the alignment unit 616 performs alignment processing on the output target image 603b converted to RGB so that the position is aligned with the scanned image 603a (S22). Next, the change amount calculation unit 611 shifts the output target image 603b by the number of first pixels (S23). In the present embodiment, the image of the output target image 603b is shifted in the horizontal direction by three pixels.

Next, the change amount calculation unit 611 generates a difference image 603c2 (for example, an image similar to FIG. 6) based on the shift image obtained in step S23 and the output target image 603b that has not been processed in step S23. (S24).

Next, the change amount calculation unit 611 sets a value obtained by adding a predetermined value for each pixel value of each pixel included in the difference image 603c2 as the first classification threshold value A, and sets a value obtained by subtracting the predetermined value as the second classification threshold value B. The threshold image 603f is generated (S25). The threshold image 603f is temporarily stored in the RAM 603.

After steps S12 and S25, the change amount calculation unit 611 performs ternation processing of the difference image 603c1 generated in step S2 based on the threshold image 603f read from the RAM 603 (S13). Next, the defect feature amount extraction unit 612 detects the streak feature amount (for example, FIG. 8) based on the classification result 603d (S14).

Then, the quality determination unit 613 compares the streak feature amount with the defect detection threshold value read from the parameter 603e, and detects the streak (S15). The quality determination unit 613 writes the streak detection result 631 in the storage unit 63. After that, the inspection processing device 5A ends the main processing.

The inspection processing device 5A according to the second embodiment described above generates a threshold image 603f defined by a classification threshold value with respect to the difference value. Then, ternation processing is performed based on the threshold image 603f. Therefore, even for the streaks generated in the non-flat region of the scanned image 603a, the streaks are quantified by the ternification process and the feature amount is extracted, so that the streak detection accuracy can be improved.

[Modification example]
In each of the above-described embodiments, the image inspection device 3 is combined with the inspection processing devices 5 and 5A, but the functions of the inspection processing devices 5 and 5A are incorporated into, for example, the PC 6 to incorporate the inspection processing devices 5 and 5A. It may be separated from the image inspection device 3. Further, the image forming apparatus 2 may have the functions of the inspection processing devices 5 and 5A, and the image forming apparatus 2 may perform an image inspection by itself. Further, by providing a server having the functions of the inspection processing devices 5 and 5A to configure the image forming system, even if the server accumulates the scanned image 603a and the output target image 603b read from the paper Sh by the image inspection device 3. Good. Then, the server may communicate with the image inspection device 3 to detect the streaks of the read image 603a received from the image inspection device 3 and transmit the streak detection result to the image inspection device 3 or the PC 6.

Further, the present invention is not limited to the above-described embodiments, and it goes without saying that various other application examples and modifications can be taken as long as the gist of the present invention described in the claims is not deviated.
For example, each of the above-described embodiments describes in detail and concretely the configurations of the apparatus and the system in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to those including all the described configurations. Further, it is possible to replace a part of the configuration of the embodiment described here with the configuration of another embodiment, and further, it is possible to add the configuration of another embodiment to the configuration of one embodiment. It is possible. It is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.
In addition, the control lines and information lines indicate those that are considered necessary for explanation, and do not necessarily indicate all the control lines and information lines in the product. In practice, it can be considered that almost all configurations are interconnected.

1 ... Image inspection system, 2 ... Image forming device, 3 ... Image inspection device, 5 ... Inspection processing device, 30 ... Image forming unit, 45 ... Reading unit, 60 ... Control unit, 603a ... Scanned image, 603b ... Output target image , 603c1, 603c2 ... Difference image, 603d ... Classification result, 603e ... Parameter, 603f ... Threshold image, 611 ... Change amount calculation unit, 612 ... Defect feature amount extraction unit, 613 ... Quality judgment unit, 615 ... Image conversion unit, 616 … Alignment part, 631… Streak detection result

Claims (8)

Of the plurality of pixels included in the scanned image read from the recording material on which the image is formed, the comparative pixels that are separated by the first pixel number in the first direction with respect to the pixel value of the pixel of interest with respect to the pixel value of interest. A change amount calculation unit that calculates the difference value of the pixel value and classifies the difference value into the first and second classification values by the classification threshold as the change amount of the pixel value.
The number of the same first classification value was counted for each second direction intersecting with the first direction of the classification result, and the number of the first count result and the number of the second classification value were counted. The second count result is obtained and included in the second count result, which is separated from the number of the first classification values included in the first count result by the number of second pixels in the first direction. A feature amount extraction unit that extracts a value obtained by adding the number of second classification values as a plurality of feature amounts of streaky defects generated in the image formed on the recording material, and a feature amount extraction unit.
A streak-like defect is detected by comparing a value calculated from a plurality of the feature amounts at the same position in the first direction with a preset defect detection threshold value, and the image formed on the recording material. An image inspection device equipped with a quality judgment unit that judges the quality of the image. When the ratio of the first feature amount and the second feature amount at the same position in the first direction is equal to or more than the defect detection threshold value, the quality determination unit determines the streak-like defect. The image inspection apparatus according to claim 1. The feature amount extraction unit is separated from the first count result at the position of the attention pixel in the first direction of the classification result by the second pixel number from the position of the attention pixel. The value obtained by adding the count result is extracted as the first feature amount, and the second count result at the position of the attention pixel in the first direction of the classification result and the position of the attention pixel are used as described above. The image inspection apparatus according to claim 2, wherein a value obtained by adding the first count result, which is separated by the number of second pixels, is extracted as the second feature amount. The image inspection apparatus according to any one of claims 1 to 3, wherein the change amount calculation unit generates the classification result of classifying the difference value based on the magnitude and the code of the difference value. The image inspection apparatus according to any one of claims 1 to 4, wherein the first direction is either a horizontal direction parallel to the printing direction or a vertical direction perpendicular to the printing direction. An image conversion unit that converts the color mode of the output target image, which is the source of the image formed by the image forming apparatus on the recording material, according to the color mode of the scanned image.
A positioning unit for aligning the position of the output target image converted by the image conversion unit with the read image is provided.
The image inspection apparatus according to any one of claims 1 to 5, wherein the change amount calculation unit changes the classification threshold value according to a change in the pixel value of the read image aligned by the alignment unit. .. The image inspection apparatus according to any one of claims 1 to 6, further comprising a reading unit that reads the image from the recording material and generates the read image. An image forming apparatus for forming an image on a recording material and an image inspection apparatus for inspecting the image formed on the recording material are provided.
The image inspection device is
Of the plurality of pixels included in the scanned image read from the recording material, the difference between the pixel values of the pixels of interest and the pixel values of the comparison pixels separated by the number of first pixels in the first direction with respect to the pixels of interest. A change amount calculation unit that calculates a value and calculates the classification result of classifying the difference value into the first and second classification values by the classification threshold as the change amount of the pixel value.
The number of the same first classification value was counted for each second direction intersecting with the first direction of the classification result, and the number of the first count result and the number of the second classification value were counted. The second count result is obtained and included in the second count result, which is separated from the number of the first classification values included in the first count result by the number of second pixels in the first direction. A feature amount extraction unit that extracts a value obtained by adding the number of second classification values as a plurality of feature amounts of streaky defects generated in the image formed on the recording material, and a feature amount extraction unit.
A streak-like defect is detected by comparing a value calculated from a plurality of the feature amounts at the same position in the first direction with a preset defect detection threshold value, and the image formed on the recording material. An image inspection system equipped with a quality judgment unit that judges the quality of the product.

Images