JP7367461B2 - Image inspection equipment and image inspection system - Google Patents

Description

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

When printing in large quantities, the operator usually performs several trial prints and makes various adjustments, and then starts actual printing after confirming from the sample that there are no problems with the printed content. However, for some reason, color misregistration or distortion may occur in the image of the actual printed paper with respect to the sample. Therefore, in recent years, an inspection system has been provided in which a reading device such as a scanner is provided on the conveyance path after the image forming device, and an image inspection device inspects the read image obtained by reading the image of each sheet to be printed out. It became so. In this inspection, the original image of the image formed on the paper is saved as the output target image. Then, the image inspection device compares an image (read image) obtained by reading the paper printed in the actual printing with a scanner and a saved output target image.

When a read image is compared with an output target image, an image defect may be detected from the read image. Types of image defects include, for example, narrow stripes or bands that appear continuously in a predetermined direction or that appear discontinuously in a predetermined direction. Such image defects are collectively referred to as streak defects. However, in the following description, the streak-like defect is also abbreviated as "streak." Streaks are defects caused by scratches or dirt on the drums and rollers of image forming devices, scanners, and other reading devices. It appears as "streak intensity") and density unevenness. Examples of the streaks include white streaks that are thinner than the original image, black streaks that are darker than the original image, and the like. Because streaks tend to occur repeatedly and are easily recognized by operators and customers, it is necessary to reliably detect streaks even during actual printing.

A technique disclosed in Patent Document 1 is known for detecting streaks. In this Patent Document 1, a second difference image is generated by taking a difference between a first difference image between an output target image and a read image, and a pixel separated by a predetermined number of pixels, and , the first number of pixels whose pixel value is larger than the first threshold value and the second number of pixels whose pixel value is smaller than the first threshold value are calculated, and the number of pixels whose pixel value is smaller than the first threshold value is calculated. A technique for determining streaks based on the ratio between the number of pixels of 1 and the number of pixels of a second type has been disclosed.

Unexamined Japanese Patent Publication No. 2017-173000

Lines appear in the sub-scanning direction or the main-scanning direction of an image formed on paper due to various factors. For example, if a charging electrode provided in an image forming apparatus is soiled with toner or the like, charging of the soiled area may not be successful, and as a result, streaks may appear in the sub-scanning direction of the image. Further, when a defect occurs in a rotating body such as a photosensitive drum, streaks appear in the main scanning direction in synchronization with the rotation period of the rotating body.

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

Streaks that occur continuously on printed matter are easily noticeable and easy for operators to see. However, the difference in pixel values of an image is often very small between areas where there are streaks and areas where there are no streaks. Therefore, even if there were streaks in the read image, the fluctuations in pixel values averaged in the sub-scanning direction were almost the same as the fluctuations in pixel values caused by density unevenness at other positions where there were no streaks. The technique disclosed in Patent Document 1 generates a second difference image by taking the difference between the first difference image and a pixel that is a predetermined number of pixels apart, but it does not create a second difference image that is visible to the operator. could not be detected.

The present invention has been made in view of this situation, and it is an object of the present invention to make it possible to detect streak-like defects that occur in read images.

In order to achieve at least one of the above-mentioned objects, an image inspection apparatus that reflects one aspect of the present invention detects attention among a plurality of pixels included in a read image read from a recording material on which an image is formed. Calculate the difference value between the pixel value of the pixel and the pixel value of a comparison pixel that is separated by a first number of pixels in a first direction with the pixel of interest as a reference, and convert the difference value into first and second classification values using a classification threshold. a change amount calculation unit that calculates the classified results as a change amount of pixel values; and a first unit that counts the number of the same first classification values in each second direction that intersects with the first direction of the classification results. and a second count result of counting the number of second classification values, and calculate the number of first classification values included in the first count result at the position of the pixel of interest and the first direction. The value obtained by adding the number of second classification values included in the second count result at the position of the comparison pixel , which is separated by the second number of pixels in the opposite direction from The number of first classification values extracted as the second feature quantity of the defect and included in the second count result at the position of the pixel of interest and the second number of pixels in the opposite direction to the first direction. A feature quantity that is obtained by adding the number of second classification values included in the first count result at the position of the comparison pixel as a first feature quantity of a streak-like defect occurring in an image formed on a recording material. The extraction unit calculates the ratio of the first feature amount to the second feature amount for each same position in the first direction, and detects a streak -like defect at a position where the ratio is equal to or higher than a preset defect detection threshold. and a quality determining section that determines the quality of the image formed on the recording material.
Note that the above image inspection apparatus is one aspect of the present invention, and an image inspection system that reflects one aspect of the present invention is also configured in the same manner as the above image inspection apparatus.

According to the present invention, since the presence or absence of a visible streak-like defect is detected with high accuracy using the characteristics of the streak, it is possible to improve the quality of an image formed on a recording material.
Problems, configurations, and effects other than those described above will be made clear by the following description of the embodiments.

It is a graph showing an example of data obtained by averaging pixel values in the sub-scanning direction. 1 is a schematic configuration diagram of an image inspection system according to a first embodiment of the present invention. 1 is a block diagram illustrating a configuration example of a control system of an image forming apparatus according to a first embodiment of the present invention. FIG. 1 is a block diagram showing a configuration example of a control system of an image inspection apparatus according to a first embodiment of the present invention. FIG. FIG. 3 is a diagram showing an example of a read image according to the first embodiment of the present invention. FIG. 3 is a diagram showing an example of a difference image according to the first embodiment of the present invention. It is a figure showing an example of a classification result concerning a 1st embodiment of the present invention. FIG. 3 is a diagram illustrating a process in which the defect feature amount extracting unit according to the first embodiment of the present invention extracts a streak feature amount. 3 is a flowchart illustrating an example of processing performed by the inspection processing device according to the first embodiment of the present invention. FIG. 7 is a diagram illustrating how the number of pixels of a specific pixel value included in a difference image according to a modification of the first embodiment of the present invention is counted in the vertical direction, and the first and second feature amounts. FIG. 2 is a block diagram illustrating a configuration example of a control system of an image inspection apparatus according to a second embodiment of the present invention. 7 is a graph showing an example of pixel values and difference values of pixels in a flat region and a non-flat region of a read image according to the second embodiment of the present invention, and a classification threshold. It is a flowchart which shows the example of the process performed by the test|inspection processing apparatus based on the 2nd Embodiment of this invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments for carrying out the present invention will be described with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functions or configurations are designated by the same reference numerals and redundant explanations will be omitted.

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

First, with reference to FIG. 2, a configuration example of an image inspection system according to the first embodiment of the present invention will be described.
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 explaining 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. 2.

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 using an electrophotographic method that uses static electricity to form an image. The image forming apparatus 2 forms a color image on a sheet of paper using, for example, a tandem format in which toner images of four colors, yellow (Y), magenta (M), cyan (C), and black (K) are superimposed. A PC (Personal Computer) 6 (see FIG. 3 described below) 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 image forming processing 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 section 11 having an automatic document feeder (ADF) 12 and an operation display section 13 . The image forming apparatus 2 also includes a printer section 10 having a paper feed tray 20 and an image forming section 30.

The image input unit 11 optically reads an image from a document on the document table of the ADF 12, performs A/D conversion on the read image, and generates image data. Note that the image input unit 11 can also read an image from a document on a platen glass.

The operation display unit 13 includes a display unit such as a liquid crystal panel, and an operation unit such as a touch sensor. The display section and the operation section are integrally formed as a touch panel, for example. The operation display unit 13 generates an operation signal representing the content of the operator's operation input to the operation unit, and supplies the operation signal to the control unit 50 (see FIG. 3, which will be described later). Further, the operation display section 13 displays the contents of the operation by the operator, setting information, etc. on the display section based on the display signal supplied from the control section 50. Note that it is also possible to configure the operation unit with a mouse, a tablet, etc., and to configure it separately from the display unit.

The paper feed tray 20 is a container that accommodates paper Sh on which image formation is performed in the image forming section 30. The paper feed trays 20 accommodate sheets of paper having different paper types, basis weights, and the like. The 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. Note that in this embodiment, an example is given in which two paper feed trays 20 are provided, but the number of paper feed trays 20 may be one, or may be three or more.

The image forming apparatus 2 is provided with a conveyance path 21 that conveys the paper Sh fed from the paper feed tray 20 to the image inspection apparatus 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 unit 36 , the conveyance path 21 extends and is connected to the conveyance path 41 of the image inspection device 3 . Furthermore, the conveyance path 21 branches on the downstream side of the fixing section 36. A reversing conveyance path 22 that joins the conveyance path 21 on the upstream side of the printer section 10 is connected to one end of the branched conveyance path 21 . The reversing conveyance path 22 is provided with a reversing section 23 for reversing the paper Sh. The sheet Sh reversed by the reversing unit 23 is returned to the upstream side of the transport path 21 through the reversing transport path 22 . Further, the sheet Sh that has been reversed due to the switching of the path may be returned to the conveyance path 21 on the downstream side of the fixing section 36 and then conveyed to the image inspection apparatus 3.

The image forming section 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 images on paper Sh. The image forming units 31Y, 31M, 31C, and 31K each include a charging section, an exposure section (all not shown), photosensitive drums 32Y, 32M, 32C, and 32K as image carriers, and developing sections 33Y, 33M, and 33C. , 33K.

The developing sections 33Y, 33M, 33C, and 33K generate electrostatic charges on the periphery of each photosensitive drum by irradiating each surface (outer periphery) of the photosensitive drums 32Y, 32M, 32C, and 32K with light according to the image. Form a latent image. The developing units 33Y, 33M, 33C, and 33K form toner images on the photoreceptor drums 32Y, 32M, 32C, and 32K by attaching toner to the electrostatic latent images.

The image forming section 30 also includes an intermediate transfer belt 34, a secondary transfer section 35, and a fixing section 36. The intermediate transfer belt 34 is a belt to which images formed on the photoreceptor 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 that have been primarily transferred onto the intermediate transfer belt 34 onto the paper Sh that has been conveyed through the conveyance path 21 .

The fixing unit 36 is disposed downstream of the secondary transfer unit 35 in the paper transport direction, and performs a fixing process on the paper Sh supplied from the image forming unit 30 and on which a color toner image has been formed. The fixing unit 36 fixes the image transferred by the image forming unit 30 on the front side of the paper Sh by heating and pressurizing the transported paper Sh. The paper Sh on which the image has been fixed by the fixing section 36 is transported to the image inspection device 3 through the transport path 21, or is transported upstream of the printer section 10 after passing through the reversing transport path 22 and being turned upside down by the reversing section 23. It is returned to Route 21. The printer section 10 forms an image on the back side of the sheet Sh, which has been turned upside down. Thereafter, the sheet Sh subjected to the fixing process by the fixing section 36 is conveyed to the image inspection device 3.

Next, a configuration example of the image inspection apparatus 3 will be explained.
The image inspection device 3 performs an image inspection to detect streaks generated in the 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 includes conveyance paths 41, 42, and 43, a switching section 44, reading sections 45a and 45b, a colorimeter 46, and conveyance paths 41, 42, and 43 for conveying the sheet Sh conveyed from the image forming apparatus 2. It has paper ejection trays 47 and 48 from which the paper sheets Sh are ejected.

The reading units 45a and 45b are each an example of an image input device such as an image sensor. The reading units 45a and 45b, for example, project light onto the surface of the paper Sh and capture reflected light from the paper Sh as image data. The reading of the image data of the paper Sh by the reading units 45a and 45b in this manner is called "reading". The reading section 45a reads the paper Sh conveyed through the conveyance path 41 from below the conveyance path 41, and the reading section 45b reads the sheet Sh conveyed through the conveyance path 41 from above the conveyance path 41. In the following description, the reading sections 45a and 45b will not be distinguished, and will be collectively referred to as "reading section 45." The reading unit 45 then 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 sheet Sh being 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 that can measure the intensity (spectrum) of reflected light for each wavelength of light, and measures the measured color density (reflection density), L*a*b* value, etc. Output. The colorimeter 46 uses, for example, a scanner (line sensor) in which a plurality of sensors (photoelectric conversion elements) (not shown) are arranged one-dimensionally over the entire paper width direction (direction orthogonal to the paper conveyance direction). Ru. When the colorimeter 46 is configured with a scanner, the image is read while moving the scanner in a direction (paper conveyance direction) perpendicular to the direction in which the scanner is arranged. Then, the colorimeter 46 measures the color density of the image formed on the paper Sh for each area obtained by dividing the area where the image is read into a mesh shape. The colorimeter 46 outputs information on the measured color density to the inspection processing device 5.

Note that the colorimeter 46 may be configured with a single sensor, and the color density of the image formed on the paper Sh may be measured by moving the sensor two-dimensionally. Alternatively, the colorimeter 46 may be configured with a plurality of sensors arranged two-dimensionally (in a matrix), and the color density of all pixels on the paper may be read by one measurement using the plurality of sensors.

The image inspection apparatus 3 includes transport paths 42 and 43 connected to a transport path 41.
The conveyance path 42 is a path that branches off from the middle of the conveyance path 41, and discharges the paper Sh inspected by the inspection processing device 5 to a paper discharge tray 47 (an example of a paper discharge section). A sheet Sh (also referred to as "normal sheet") whose image is determined to be normal by the inspection processing device 5 is discharged to the sheet discharge tray 47 .

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

The switching unit 44 switches the conveyance direction of the paper Sh so that the paper Sh is conveyed to either of the conveyance paths 42 and 43. Note that if the image inspection apparatus 3 has only one paper ejection tray 47, normal sheets and abnormal sheets are mixed and ejected. In this case, the normal paper and the abnormal paper are ejected, for example, with a slight shift in the direction perpendicular to the ejecting direction.

The paper Sh conveyed to the image inspection device 3 is a printed matter with images formed on both sides or one side. The image inspection device 3 reads the images 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 is capable of forming images on both sides of the paper Sh, an example is given in which 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 transported from an image forming device capable of forming an image on only one side of the paper Sh.

[Configuration 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 a control system of the image forming apparatus 2. As shown in FIG.
The image forming apparatus 2 mainly includes a communication I/F section 51, a paper transport section 24, an image input section 11, an image forming section 30, a control section 50, a storage section 52, a fixing section 36, and an operation display section 13. Be prepared.

The communication I/F unit 51 is an interface that transmits and receives data to and from the 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 conveyance section 24 drives the conveyance path 21 shown in FIG. 2, conveyance rollers (not shown) provided on the reversal conveyance path 22, and the reversal section 23 under the control of the control section 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 programs executed by the CPU 501 of the control unit 50 or data used when executing the programs. The CPU 501 controls each part of the image forming apparatus 2 by reading a program stored in the ROM 502.
In the RAM 503, variables and parameters generated during arithmetic processing by the CPU 501 are temporarily written.

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. The input image processing unit 504 also performs image processing on image data acquired from a document read by the image input unit 11 with the ADF 12 or image data acquired from an external source, and creates image data for printing. This printing image data is sent to the image forming section 30 and the image inspection device 3. In the image inspection apparatus 3, the print image data is saved as an output target image 603b (see FIG. 4, which will be described later).

The control unit 50 controls the paper transport unit 24 to drive the transport rollers and 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. The control unit 50 also controls the image forming unit 30 to form an image on the paper Sh. The control unit 50 also 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 various setting screens for inputting various operation instructions and setting information, and an operation screen for displaying various processing results. Display on panel. The information displayed on the operation display section 13 also includes a 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 a program, data obtained by executing the program, and the like. For example, the storage unit 52 stores information such as image forming conditions for each density level. Note that the storage unit 52 may store a program executed by the CPU 501.

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

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

The communication I/F section 61 is an interface that transmits and receives data to and from the image forming apparatus 2 via a network. As the communication I/F unit 61, for example, a NIC is used.
The paper conveyance section 62 drives a conveyance roller (not shown) provided on the conveyance path 41 shown in FIG. 2 under the control of the control section 60.

As described above, the reading unit 45 reads the images formed on the top and bottom surfaces of the paper Sh being conveyed through the conveyance path 41. In this 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 a read image 603a. Furthermore, the RIP-processed printing image data that the inspection processing device 5 receives from the image forming device 2 is stored in the RAM 603 as an output target image 603b. As explained in the second embodiment described later, the output target image 603b may also be used for inspecting the read image 603a. Note that the read image 603a and the output target image 603b may be stored in the storage unit 63 configured with a large-capacity HDD or the like. Furthermore, the color density information output from the colorimeter 46 to the image inspection apparatus 3 may be included in the read image 603a and the output target image 603b.

The control unit 60 includes a CPU 601, 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 of the image inspection apparatus 3 by reading a program stored in the ROM 602. When the CPU 601 executes the program read from the ROM 602, the functions of the change amount calculation section 611, the defect feature amount extraction section 612, and the quality judgment section 613 are realized.

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

In the RAM 603, variables and parameters generated during arithmetic processing by the CPU 601 are temporarily written. 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 parameters 603e include various values set by the control unit 60 or the operator. The parameter 603e includes, for example, a defect detection threshold value for detecting streaks from the streak feature amount described later. The change amount calculation unit 611, defect feature amount extraction unit 612, and quality determination unit 613 perform various processes based on various values read from the parameter 603e.

The change amount calculation unit 611 calculates the difference between the pixel value of a pixel of interest among a plurality of pixels included in the read image 603a and the pixel value of a comparison pixel that is separated by a first number of pixels in a first direction with respect to the pixel of interest as a reference. A classification result 603d in which the difference value is classified into first and second classification values using a classification threshold is calculated as the amount of change in pixel value. Hereinafter, the first direction will be described as the main scanning direction and the second direction as the sub-scanning direction. However, if the direction of the line 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 this embodiment, the first number of pixels is "3".

For example, the change amount calculation unit 611 calculates a difference value between the pixel value of a pixel of interest selected from a plurality of pixels included in the read image 603a and the pixel value of a comparison pixel. Then, the change amount calculating unit 611 generates a difference image 603c1 including difference values calculated by performing similar processing on other pixels of the read image 603a. At this time, the change amount calculation unit 611 calculates the difference between a shifted image (not shown) obtained by shifting the read image 603a by a predetermined number of pixels in the horizontal or vertical direction and the read image 603a before the shift, and generates a difference image. It is possible to generate 603c1. The shift represents the distance between pixels for determining a comparison pixel with respect to the pixel of interest. Details of the difference image 603c1 will be explained later with reference to FIG. 6.

Further, the change amount calculation unit 611 generates a classification result 603d in which each pixel is classified into a plurality of types as a change amount based on the magnitude and sign of the difference value of each pixel included in the difference image 603c1. As described above, the classification result 603d is expressed as a result of the change amount calculation unit 611 classifying (ternarizing) the difference value using the classification threshold for each of the plurality of pixels included in the difference image 603c1. The classification threshold is a value set in the parameter 603e.

In this embodiment, the process in which the change amount calculation unit 611 converts the difference value of each pixel included in the difference image 603c1 into three values for each pixel by referring to the classification threshold value is referred to as "multi-value conversion". Depending on the classification threshold value, the change amount calculation unit 611 may convert the difference value of the difference image 603c1 into a multivalued form such as binarization, quaternary value, or the like. Further, the classification threshold is a value that is set in advance before the start of the image inspection, and may be set to a different value depending on the resolution of the read image 603a, the type of image formed on the paper Sh, etc. Details of the classification result 603d will be explained later with reference to FIG.

The defect feature amount extraction unit 612 extracts the feature amount of a streak-like defect (“streak feature amount”) that occurs in the image formed on the paper Sh based on the amount of change calculated based on a plurality of pixels in the sub-scanning direction. ) is extracted. For example, when the direction in which streaks occur is in the sub-scanning direction, the defect feature extracting unit 612 refers to the classification result 603d in the sub-scanning direction for each predetermined position in the main-scanning direction, and refers to the averaging result (ternary value). The line features are extracted from the averaged results). The ternary averaging result is the result obtained by the defect feature extracting unit 612 averaging the difference values that the change amount calculating unit 611 classifies using the classification threshold value and converts into multivalued values. It is shown in a graph expressed by the ternary average value shown below. Details of the streak feature amount will be explained later with reference to FIG. 8.

Then, the defect feature 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 of counting the number of pixels for each classification of the classification result 603d (described later). (see Figure 10). The defect feature extraction unit 612 extracts the count result obtained at a position that is a first number of pixels away from the pixel of interest in the opposite direction to the direction in which the comparison pixel is located when the direction in which streaks occur is the sub-scanning direction. Features can be extracted by referring to .

The quality determining unit 613 detects streak-like defects by comparing values calculated from a plurality of streak feature amounts with a preset defect detection threshold for each same position in the main scanning direction, and detects streak-like defects formed on the paper Sh. judge the quality of the image. At this time, the quality judgment unit 613 detects a streak-like defect based on the ratio between the count result at a predetermined position of the pixel of interest in the main scanning direction and the count result referenced at a position away from the pixel of interest (described later). (see Figure 10).

The quality determining unit 613 determines that the read image 603a is normal if no streaks are detected from the streak feature amount. On the other hand, if the quality determining unit 613 detects streaks from the streak feature amount, it determines that the read image 603a is abnormal. The quality determining unit 613 then 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 the external storage device 4 connected to the image inspection apparatus 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), etc. 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 check the contents. Note that the streak detection result 631 may be transferred to and stored in a cloud server (not shown) or PC 6 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 to the image forming apparatus 2 or the PC 6 via the communication I/F unit 61 as necessary. The image forming apparatus 2 can display the streak detection result 631 on the operation display section 13. Therefore, the operators of the image forming apparatus 2 and the image inspection apparatus 3 can check the contents of the streak detection result 631 from the operation display section 13. Further, the operator can also check the contents of the streak detection result 631 from the PC 6.

The control unit 60 selects a paper discharge tray (an example of a paper discharge destination) for the paper Sh conveyed through the conveyance path 41 according to the streak detection result 631. For example, the control unit 60 operates the switching unit 44 to discharge the normal paper transported to the transport path 42 to the paper ejection tray 47, and to discharge the abnormal paper transported to the transport path 43 to the paper ejection tray 48. Make paper.

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

Next, examples of read images, image shifts, difference images, classification results, and streak detection will be explained in order.
FIG. 5 is a diagram showing an example of a read image 603a. The read image 603a shows the pixel value of one of the R, G, and B channels for each pixel represented by one square in the figure.

The pixel value takes a number between "0" and "255" for each R, G, and B channel. 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 (for example, three pixels) in the horizontal direction when viewed from the pixel of interest. Note that 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 true for other pixels.

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

The difference image 603c1 generated by the change amount calculation unit 611 as described above is an image in which the difference value between the pixel of interest and the comparison pixel is stored at the position of the pixel of interest. For example, since the pixel value of the target pixel in the read 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 calculations are performed on other pixels included in the read image 603a, and a difference image 603c1 is generated.

As described above, the difference image 603c1 stores a difference value for each pixel of interest. However, if the difference value remains unchanged, it is difficult to detect the streak because the difference between the area where there is a line in the read image 603a and the area where there is no line is small. Therefore, two threshold values are set for the parameter 603e, and the change amount calculation unit 611 uses the two threshold values to perform ternarization processing to obtain a 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 this embodiment, "+8" is set as the first classification threshold and "-8" is set as the second classification threshold in the parameter 603e. The change amount calculation unit 611 replaces the difference value of a pixel whose difference value is larger than the first classification threshold value with "255", and replaces the difference value of a pixel with a difference value smaller than the second classification threshold value with "0". Further, the change amount calculation unit 611 replaces the difference value of a pixel whose difference value is greater than or equal to the second classification threshold and less than or equal to the first classification threshold to “128”. FIG. 7 shows that the difference value of each pixel included in the difference image 603c1 has been replaced with one of "0", "128", and "255".

Note that the first classification threshold and the second classification threshold are adjusted based on the density of the streak (gradation difference in pixel values) that the quality determination unit 613 detects. For example, in an area without streaks, a threshold value may be set such that the difference values of most pixels are replaced with "128".

Here, the extraction process of the streak feature amount will be explained with reference to FIG. 8.
FIG. 8 is a diagram showing how the defect feature extraction unit 612 extracts the streak feature.

In the upper part of FIG. 8, pixel values are sub-scanned for each specific position indicated by the main-scanning position in a flat image area (referred to as a "flat area") that is known in advance in the read image 603a. A graph of the averaged results averaged by direction is shown.
The graph showing the averaged pixel values shows that there is a streak at the main scanning position "14". It can be seen that the pixel values at the position where the stripe is located vary a little more than the surrounding pixel values. However, it is not clear whether this variation is caused by noise or streaks.

In the middle part of FIG. 8, a graph of the ternary averaging results is shown.
The defect feature extraction unit 612 refers to the classification result 603d in the sub-scanning direction and averages the values of each pixel. Through this process, the defect feature amount extraction unit 612 averages the values (ternarized values) of each pixel of the classification result 603d in the sub-scanning direction, and performs ternarization averaging to represent the ternary average value in a graph. Get results. If there is no noise in the read image 603a, the ternary average value will be 128. The main scanning position indicated by a broken line circle in the figure is "10", and the position "14" has a large difference from "128". However, since the difference between the ternary average values at these positions and the surrounding ternary average values is small, it is difficult to detect them as streaks and separate them from noise.

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

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

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

First, the change amount calculation unit 611 shifts the read image 603a (eg, FIG. 5) read from the RAM 603 and input by a first number of pixels (eg, 3 pixels) (S1). Then, the change amount calculation unit 611 generates a difference image 603c1 (for example, FIG. 6) based on the shifted 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 ternarization processing on the difference image 603c1 based on the first classification threshold and the second classification threshold read from the parameter 603e, and classifies the difference image 603c1 including the ternarized value for each pixel. A result 603d (eg, FIG. 7) is generated (S3).

Next, the defect feature amount extracting unit 612 extracts the streak feature amount (for example, the lower part of FIG. 8) based on the classification result 603d (S4). The quality determining unit 613 then compares the extracted streak feature amount with the defect detection threshold read out from the parameter 603e to detect streaks (S5) and determines the quality of the read image 603a. The quality determination unit 613 writes the streak detection result 631 into the storage unit 63. After that, the inspection processing device 5 ends this process.

In the inspection processing device 5 according to the first embodiment described above, after obtaining the difference image 603c1 by calculating the difference between the shifted image obtained by shifting the read image 603a by several pixels and the read image 603a, Streaks in the read image 603a are detected by converting the difference image 603c1 into three values and extracting the streak feature amount. The inspection processing device 5 can detect the stripes even if the area where the stripes occur in the read image 603a is flat, so that the detection accuracy of the stripes is improved.

[Modification of the first embodiment]
Although FIG. 8 shows an example in which the classification results are averaged, the defect feature extraction unit 612 may detect streaks based on the ratio of the classification values counted. Here, processing by the defect feature extracting unit 612 and quality determining unit 613 according to this modification will be described.

The defect feature extraction unit 612 extracts a first count result obtained by counting the number of the same first classification values in each sub-scanning direction intersecting the main scanning direction of the classification result 603d, and the number of second classification values. The number of first classification values included in the first count result and the number of first classification values included in the second count result separated by the second number of pixels in the main scanning direction are obtained. A value obtained by adding the number of classification values of No. 2 is extracted as a plurality of feature amounts of a streak-like defect occurring in an image formed on a recording material.

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

A specific method for detecting streaky defects will be described with reference to FIG. 10.
FIG. 10 is a diagram showing how 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 in the upper part of FIG. 10, the defect feature extraction unit 612 obtains first and second count results. "+8" shown in the figure represents the first classification threshold explained in FIG. 7, and "-8" represents the second classification threshold. FIG. 10 shows the first count result obtained by the defect feature extraction unit 612 counting the number of pixels including a pixel value greater than "+8" in the sub-scanning direction of the difference image 603c1, and the sub-scanning result of the difference image 603c1. A second count result obtained by counting the number of pixels including a pixel value smaller than "-8" in the scanning direction is shown.

In other words, the first and second count results are determined by the defect feature extraction unit 612, which calculates the number of classification values included in the classification result 603d for each classification value (for example, for each “0” or “255”) in the sub-scanning direction. ) can also be said to be the value counted. For this reason, the defect feature extraction unit 612 uses a first count result obtained by counting the number of pixels including a classification value larger than "200", for example, with respect to the classification value of the pixel included in the classification result 603d, and a difference image. A second count result may be obtained by counting the number of pixels including a classification value smaller than "100" in the sub-scanning direction of 603c1.

FIG. 10 shows how the first and second count results are arranged so that the main scanning positions match. Then, the defect feature extracting unit 612 adds the counted result to the counted result in a comparison pixel row that is horizontally separated by three pixels (an example of the second number of pixels). At this time, the defect feature extracting unit 612 uses the first count result at the position of pixel 71 of the pixel column of interest in the main scanning direction of the classification result 603d and the second number of pixels (for example, , 3 pixels) and the second count result is extracted as the first feature quantity. Furthermore, the defect feature extracting unit 612 uses the second count result at the position of the pixel 72 of the pixel column of interest in the main scan of the classification result 603d, and the second count result at the position of the pixel 72 of the pixel column of interest in the main scanning, and the second count result at the position of the pixel 72 of the pixel column of interest in the main scanning of the classification result 603d. A value obtained by adding the first count result is extracted as a second feature quantity.

The total value of the results counted by the defect feature amount extraction unit 612 is expressed as a first feature amount and a second feature amount shown in the lower part of FIG. 10 . The first feature amount is the sum of the count result of pixels smaller than "-8" in the pixel column of interest and the count result of pixels larger than "+8" in the comparison pixel column. For example, the value "18" (first feature quantity) which is the sum of the count result "9" of pixel 72 in the pixel column of interest and the count result "9" of pixel 81 in the comparison pixel column is the value "18" (first feature quantity) of pixel 91 of the first feature quantity. is stored in

Further, the second feature amount is the sum of the count result of pixels larger than "+8" in the pixel column of interest and the count result of pixels smaller than "-8" in the comparison pixel column. For example, the value "1" (second feature quantity) that is the sum of the count result "1" of pixel 71 in the pixel column of interest and the count result "0" of pixel 82 in the comparison pixel column is the value "1" (second feature quantity) of pixel 92 of the second feature quantity. is stored in

Then, the quality determining unit 613 calculates the ratio between the first feature amount and the second feature amount for each same pixel column. If this ratio is 10 times or more, the quality determining unit 613 detects a streak at the main scanning position of the pixel column of interest. In FIG. 10, since the ratio of 18/1=18 (times) is calculated, a streak is detected in the pixel column of interest. Note that the ratio threshold used for detecting streaks is stored in the parameter 603e, and can be changed by the operator as appropriate.

Furthermore, if the first classification threshold and the second classification threshold shown in FIG. 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.

Note that for wide stripes, the influence of the stripes (changes in pixel values) is gentle. Therefore, if the position of a pixel extracted as a comparison pixel is too close to the pixel of interest, the difference between the pixel and the comparison pixel becomes small, making it impossible to detect a streak. On the other hand, if the comparison pixel is too far away from the pixel of interest, streaks occurring in a narrow flat area cannot be detected.

Therefore, the first number of pixels calculated by the change amount calculation unit 611 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 difference values calculated for each of a plurality of different values are stored at the position of the pixel of interest. By setting a plurality of shift numbers of comparison pixels to be shifted with respect to the pixel of interest in the parameter 603e, the change amount calculation unit 611 calculates the difference between one pixel of interest and comparison pixels shifted by different shift numbers. , the presence or absence of streaks may be analyzed in parallel. Through such processing, the defect feature extracting unit 612 may extract the streak feature from each of the plurality of difference images 603c1, and the quality determining unit 613 may detect the streak from the extracted streak feature. Thereby, it is possible to detect the streaks appearing in the read image 603a, regardless of the thickness of the streaks.

[Second embodiment]
<Detection of streaks appearing in areas other than flat image areas>
In the embodiment described above, an example of processing for detecting streaks appearing in a flat area in the read image 603a has been described. In the case of a flat area, the classification threshold may be changed depending on the density of the stripe to be detected (gradation difference in pixel values). Therefore, the change amount calculation unit 611 extracts only the flat area from the read image 603a to generate a difference image 603c1, and then the defect feature extraction unit 612 extracts the streak feature, and the quality determination unit 613 extracts the flat area from the read image 603a. It is sufficient to detect streaks by targeting only the areas that have been detected.

However, in actual printed matter, not only flat areas but also non-flat image areas (referred to as "non-flat areas") appear. For example, streaks on a non-flat area where there is a gradation in which the amount of variation in pixel values is small are noticeable. Therefore, in the second embodiment, a process in which the inspection processing apparatus 5A detects streaks appearing in a non-flat area will be described.

FIG. 11 is a block diagram showing a configuration example of a control system of the image inspection apparatus 3. As shown in FIG. In the inspection processing device 5A included in the image inspection device 3 according to the present embodiment, when the RIP image used to form an image on the paper Sh is sent from the image forming device 2 to the inspection device 3A, the RIP image is converted into a printed material. The amount of variation in pixel values in the non-flat region is extracted, and the threshold value for ternarization is varied based on the extracted amount of variation.

The control unit 60 of the inspection processing device 5A includes an image conversion unit 615 and an alignment unit 616 in addition to the change amount calculation unit 611, defect feature amount extraction unit 612, and quality determination unit 613 according to the first embodiment described above. Equipped with. Also in this embodiment, each function of the image conversion section 615 and the alignment section 616 is realized by the CPU 601 executing the program read from the ROM 602.

The output target image 603b stored in the RAM 603 is a bitmap image that has been subjected to rasterization processing (RIP processing) in advance by the control unit 50 of the image forming apparatus 2. This output target image 603b becomes the source of the image that the image forming apparatus 2 forms on the paper Sh. Note that an image determined in advance to be correct by the operator 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 to form an image on the paper Sh by the image forming apparatus 2, the CMYK color mode is set. Therefore, the image conversion unit 615 performs image conversion to match the color mode of the output target image 603b to the color mode of the read image 603a. Here, the color mode of the read 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 on the assumption that the color mode has been converted to RGB.

The alignment unit 616 aligns the printing positions of the output target image 603b and the read image 603a read from the sheet 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 to the position of the output target image 603b stored in the RAM 603 in advance.

Then, the change amount calculation unit 611 generates a difference image 603c2 by calculating the difference between the output target image 603b and an image obtained by shifting the output target image 603b . The difference image 603c2 is stored in the RAM 603 together with the difference image 603c1, which is obtained by calculating the difference between the shifted image of the read image 603a and the read image 603a before shifting, as described in the first embodiment.

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

FIG. 12 is a graph showing an example of pixel values and difference values of pixels in a flat region and a non-flat region of the output target image 603b subjected to RIP processing, and classification threshold values. 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). Further, the flat region and the non-flat region are defined by the difference value graph shown in the upper part of FIG. 12 .

The graph at the bottom of FIG. 12 represents fluctuations in pixel values of the output target image 603b that has been subjected to RIP processing. In addition, the graph on the upper side of FIG. 12 is the difference obtained by subtracting the pixel value obtained by shifting the output target image 603b by three pixels in the horizontal direction from the pixel value of the output target image 603b in the lower graph of FIG. Represents fluctuations in value. In the figure, the first classification threshold A and the second classification threshold B are written as "threshold A" and "threshold B", respectively.

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

For example, the difference value is represented by a graph of a line L10. As shown in the graph of the line L10, the difference value in the non-flat area gradually decreases from main scanning position "7" to "9", 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 the main scanning position "23" to "30", gradually decreases from "30" to "33", and returns to the original value "0".

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

In the following description, when the first classification threshold A and the second classification threshold B are not distinguished, they are collectively referred to as "classification threshold". The classification threshold is stored in parameter 603e. The classification threshold values are all referred to by the change amount calculation unit 611 in order to ternarize the pixels specified at the main scanning position of the read image 603a.

FIG. 13 is a flowchart illustrating an example of processing performed by the inspection processing apparatus 5A according to the second embodiment. In this process, the processes in steps S11 and S12 are similar to the processes in steps S1 and S2 in FIG. Therefore, after explaining the process from step S21 onwards, the process from step S13 onwards will be explained.

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). Through this process, the image conversion unit 615 adjusts the color mode of the output target image 603b (RIP image) received by the image inspection apparatus 3 from the image forming apparatus 2 to the color mode of the read image 603a.

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

Next, the change amount calculation unit 611 generates a difference image 603c2 (for example, an image similar to that in FIG. 6) based on the shifted 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 to each pixel value of each pixel included in the difference image 603c2 as a first classification threshold A, and a value obtained by subtracting the predetermined value as a second classification threshold B. A 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 ternarization processing on the difference image 603c1 generated in step S2 based on the threshold image 603f read from the RAM 603 (S13). Next, the defect feature extraction unit 612 detects a streak feature (for example, FIG. 8) based on the classification result 603d (S14).

Then, the quality determining unit 613 detects a streak by comparing the streak feature amount with the defect detection threshold read out from the parameter 603e (S15). The quality determination unit 613 writes the streak detection result 631 into the storage unit 63. After that, the inspection processing device 5A ends this process.

The inspection processing device 5A according to the second embodiment described above generates a threshold image 603f defined by a classification threshold for the difference value. Then, ternarization processing is performed based on the threshold image 603f. Therefore, since the streaks occurring in the non-flat area of the read image 603a are also converted into three values by the ternarization process and feature amounts are extracted, it is possible to improve the accuracy of detecting the streaks.

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

Further, the present invention is not limited to the embodiments described above, and it goes without saying that various other applications and modifications can be made without departing from the gist of the present invention as set forth in the claims.
For example, in each of the embodiments described above, configurations of devices and systems are explained in detail and specifically in order to explain the present invention in an easy-to-understand manner, and the embodiments are not necessarily limited to having all the configurations described. Furthermore, it is possible to replace a part of the configuration of the embodiment described here with the configuration of other embodiments, and it is also possible to add the configuration of another embodiment to the configuration of a certain embodiment. It is possible. Furthermore, it is also possible to add, delete, or replace some of the configurations of each embodiment with other configurations.
In addition, the control lines and information lines are shown to be necessary for explanation purposes, and not all control lines and information lines are necessarily shown in the product. In reality, almost all components may be considered to be interconnected.

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

Claims (6)

Among a plurality of pixels included in a read image read from a recording material on which an image is formed, the pixel value of a pixel of interest is compared to that of a comparison pixel located a first number of pixels in a first direction with respect to the pixel of interest as a reference. a change amount calculation unit that calculates a difference value of pixel values, and calculates a classification result of classifying the difference value into first and second classification values as a change amount of the pixel value;
A first count result in which the number of the same first classification values was counted in each second direction intersecting the first direction of the classification result, and the number of the second classification values was counted. A second count result is obtained, and the number of first classification values included in the first count result at the position of the pixel of interest is separated by a second number of pixels in a direction opposite to the first direction. , and the number of second classification values included in the second count result at the position of the comparison pixel, as a second characteristic amount of the streak-like defect occurring in the image formed on the recording material. The number of first classification values extracted and included in the second count result at the position of the pixel of interest and the comparison pixel that is separated by the second number of pixels in the opposite direction to the first direction. a feature quantity that is extracted as a first feature quantity of a streak-like defect occurring in the image formed on the recording material ; a value obtained by adding the number of second classification values included in the first count result at the position; an extraction section;
A ratio of the first feature amount to the second feature amount is calculated for each same position in the first direction, and a streak-like defect is detected at a position where the ratio is calculated, which is equal to or higher than a preset defect detection threshold. and a quality determination unit that determines the quality of the image formed on the recording material. The image inspection apparatus according to claim 1 , wherein the change amount calculation unit generates the classification result by classifying the difference value based on the magnitude and sign of the difference value. The image inspection apparatus according to claim 1 or 2 , 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 a color mode of an output target image, which is a source of an image formed on the recording material by the image forming apparatus, in accordance with a color mode of the read image;
comprising a positioning unit that aligns the output target image image-converted by the image conversion unit and the read image;
The image inspection apparatus according to any one of claims 1 to 3 , wherein the change amount calculation unit changes the classification threshold according to a change in pixel values of the read image aligned by the alignment unit. . The image inspection apparatus according to any one of claims 1 to 4, further comprising a reading section that reads the image from the recording material and generates the read image. An image forming apparatus that forms an image on a recording material, and an image inspection apparatus that inspects the image formed on the recording material,
The image inspection device includes:
A difference between a pixel value of a pixel of interest among a plurality of pixels included in a read image read from the recording material and a pixel value of a comparison pixel located a first number of pixels in a first direction with respect to the pixel of interest as a reference. a change amount calculation unit that calculates a classification result of classifying the difference value into first and second classification values using a classification threshold as a change amount of the pixel value;
A first count result in which the number of the same first classification values was counted in each second direction intersecting the first direction of the classification result, and the number of the second classification values was counted. A second count result is obtained, and the number of first classification values included in the first count result at the position of the pixel of interest is separated by a second number of pixels in a direction opposite to the first direction. , and the number of second classification values included in the second count result at the position of the comparison pixel, as a second characteristic amount of the streak-like defect occurring in the image formed on the recording material. The number of first classification values extracted and included in the second count result at the position of the pixel of interest and the comparison pixel that is separated by the second number of pixels in the opposite direction to the first direction. a feature quantity that is extracted as a first feature quantity of a streak-like defect occurring in the image formed on the recording material ; a value obtained by adding the number of second classification values included in the first count result at the position; an extraction section;
A ratio of the first feature amount to the second feature amount is calculated for each same position in the first direction, and a streak-like defect is detected at a position where the ratio is calculated, which is equal to or higher than a preset defect detection threshold. and a quality determination unit that determines the quality of the image formed on the recording material.

Images