JP2021071298A - 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, for each pixel of interest in a main scan direction, a difference value between the pixel value of the pixel of interest and the pixel value of a comparison pixel separate from the pixel of interest by a first number of pixels in the main scan direction, among a plurality of pixels included in a read image having been read from a recording material on which an image is formed, then combining a difference value separate by a second number of pixels in the main scan direction, and taking, as a change amount of pixel values, a classification result obtained by classifying the combined value of the difference values into a plurality of classified values by a classification threshold; a feature quantity extraction unit 612 for extracting the feature quantity of a steak-like defect occurring in the image formed on the recording material, on the basis of an equalization result obtained by equalizing the classified value of classification result in a sub-scan direction; and a quality determination unit 613 for comparing the feature quantity with a preset defect detection threshold to detect the steak-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. Here, the streaks appearing in the scanned image will be described with reference to FIG.

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.

Since the scanned image shown in FIG. 1 is a flat image, it is expected that the pixel values will be substantially constant when the pixel values are averaged. However, in reality, it is assumed that two streaks are generated in the sub-scanning direction at the main scanning position shown by the broken line. In order to improve the quality of printed matter, it is necessary to correctly detect two streaks. However, when thin streaks (for example, streaks that are only about the width of the scanned pixel) occur in the sub-scanning direction of the scanned image generated by scanning the paper, the streaks straddle the width of several pixels adjacent to the main scanning direction. It may end up. In this case, since the pixel value of the pixel straddling the streaks is affected by the pixel value of the background pixel, the value is smaller than the original pixel value, and the occurrence of the streaks cannot be detected accurately. Even if the technique disclosed in Patent Document 1 is used, if the streaks straddle the width of several pixels adjacent to the main scanning direction, the streaks generated in the sub-scanning direction cannot be detected accurately.

The present invention has been made in view of such a situation, and an object of the present invention is to detect streak-like defects that straddle a width of several adjacent pixels so that the quality of an image can be judged.

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. After calculating the difference value between the pixel value of the pixel and the pixel value of the comparison pixel separated by the number of first pixels in the first direction from the pixel of interest for each pixel of interest in the first direction, the first is in the first direction. The change amount calculation unit that concatenates the difference values separated by the number of pixels by two pixels and classifies the concatenated values into multiple classification values by the classification threshold, and the change amount calculation unit that calculates the change amount of the pixel value, and the classification result A feature amount extraction unit that extracts the feature amount of streak-like defects generated in the image formed on the recording material based on the averaging result obtained by averaging the classification values in the second direction intersecting the first direction. The feature amount is compared with a preset defect detection threshold to detect streaky defects, and a quality determination unit for determining the quality of an image formed on a recording material is provided.
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, it is possible to accurately detect streak-like defects straddling a width of several adjacent pixels and determine the quality of an image, so that the quality of an image formed on a recording material is 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 contains the streak to be detected which concerns on 1st Embodiment of this invention, and the classification result. It is a figure which shows the state of extracting the streak feature amount from the classification result which concerns on 1st Embodiment of this invention. It is a figure which shows the relationship between the two lines which concerns on 1st Embodiment of this invention, and a scanning line. It is a figure which shows the example of the process which calculates the pixel value stored for each pixel of the scanned image which concerns on 1st Embodiment of this invention. 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 flowchart which shows the example of the front-rear value concatenation processing shown in step S3 of FIG. 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>
By taking the difference between the pixel of interest included in the scanned image and the comparison pixel near the pixel of interest, the present inventor is inseparable from the noise as shown in FIG. 1 and can be visually recognized by the operator. We have invented an image inspection device that detects streaks while reducing the effect of density unevenness. 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 10.

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 determines the pixel value of the attention pixel 71 and the pixel value of the comparison pixel 72 separated by the first pixel number in the main scanning direction from the attention pixel 71 among the plurality of pixels included in the scanned image 603a. After calculating the difference value for each pixel 71 of interest in the main scanning direction, the difference values separated by the number of second pixels in the main scanning direction were concatenated, and the concatenated values were classified into a plurality of classification values by the classification threshold. The classification result 603d is calculated as the amount of change in the pixel value. Examples of the attention pixel 71 and the comparison pixel 72 are shown in FIG. 5, which will be described later. 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 sets the position of the attention pixel 71 with the difference value between the pixel value of the attention pixel 71 selected from the plurality of pixels included in the scanned image 603a and the pixel value of the comparison pixel 72 as the change amount. Store. Then, the change amount calculation unit 611 performs the same difference processing on the other pixels of the read image 603a to generate the difference image 603c1. 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 the pixels for determining the comparison pixel 72 with respect to the pixel of interest 71. 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. Here, 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 (FIG. 5 described later). Lower row). 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. 5 described later.

When the direction in which the streaks are generated is the sub-scanning direction, the defect feature amount extraction unit 612 sets the classification value of the classification result 603d for each predetermined position in the main scanning direction in the same direction as the streak-like defect to be detected (secondary). The averaging result (ternation averaging result) averaged in the scanning direction) is calculated. Then, the defect feature amount extraction unit 612 extracts the feature amount of the streak-like defect (referred to as “streak feature amount”) from the averaging result (ternation 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 the graph represented by the ternary average value shown in the middle row. The details of the streak feature amount will be described with reference to FIG. 8 described later.

The quality determination unit 613 compares the streak feature amount with the preset defect detection threshold along the main scanning direction, and based on the presence or absence of detectable streak-like defects, the image formed on the paper Sh. Judge quality. 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, the procedure for extracting the streak feature amount from the scanned image will be described with reference to FIGS. 5 and 6.
FIG. 5 is a diagram showing an example of a scanned image 603a including a streak 70 to be detected and a classification result 603d.

The enlarged view (1) of the scanned image 603a in the upper part of FIG. 5 shows that a streak 70 to be detected is generated in the center of the scanned image 603a and in the sub-scanning direction. As shown in FIG. 1, the data obtained by averaging the pixel values in the sub-scanning direction has a large fluctuation cycle of density unevenness, so that the streaks 70 may not be detected reliably.

Therefore, the change amount calculation unit 611 selects the pixel of interest 71, selects a pixel near the pixel of interest 71 as the comparison pixel 72, and takes the difference between the pixel of interest 71 and the comparison pixel 72. At this time, the change amount calculation unit 611 takes the difference between the comparison pixel 72 and the pixel value in the direction orthogonal to the streak 70 to be detected with respect to the read image 603a. In this example, the difference between the comparison pixel 72 in the main scanning direction and the pixel value is taken with respect to the pixel of interest 71. The closer the pixels to be compared, the less affected by the density unevenness, but if the pixels to be compared are too close, the influence of streaks cannot be detected. Therefore, the change amount calculation unit 611 compares with pixels separated by half or more of the width of the streak 70 to be detected. Then, the change amount calculation unit 611 generates a difference image 603c1 in which the difference value is stored at the position of the pixel of interest 71.

Next, the defect feature amount extraction unit 614 extracts the feature amount of the streaks based on the difference value of each pixel included in the difference image 603c1 generated by the change amount calculation unit 611. Here, when the defect feature amount extraction unit 614 takes a difference value in a direction orthogonal to the streak (for example, the main scanning direction), the comparison pixel 72 comes to the streak position and the attention pixel 71 is the streak. A large value whose sign is opposite to that when the position is reached can be obtained (see the graph (3) of FIG. 6 described later).

However, although the value of the defect feature amount obtained from the difference value is larger than that in the place where there is no streak, the value itself is small. Therefore, the change amount calculation unit 611 classifies the values into three values according to whether the difference value is larger than the first classification threshold value A or smaller than the second classification threshold value B, and obtains the classification result 603d. The first classification threshold value A is a value larger than the second classification threshold value B. 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 enlarged view (2) of the classification result 603d in the lower part of FIG. 5 shows an example in which the enlarged view (1) of the scanned image 603a in the upper part of FIG. 5 is quantified. The classification result 603d is obtained by the change amount calculation unit 611 ternating the difference value of each pixel obtained from the read image 603a. The classification result 603d is represented as having each pixel replaced with a value of any one of "0", "128", and "255". Here, for the sake of simplicity, an example of the classification result 603d colored for each pixel is shown. In order to obtain such a classification result 603d, appropriate multi-value increase is required. Therefore, in the present embodiment, the classification threshold value referred to in the multi-value processing is changed according to the region of the scanned image 603a.

FIG. 6 is a diagram showing how the streak feature amount is extracted from the classification result 603d.
The graph (1) in the upper part of FIG. 6 shows an example of a ternary average value. The defect feature amount extraction unit 614 calculates a quantified average value obtained by averaging the classification result 603d in the streak direction for detection. In this example, it is assumed that the streak direction to be detected by the operator is the sub-scanning direction. Then, the ternary average value is represented as a graph in which a peak is formed when the main scanning position is “15” and a valley is formed when the main scanning position is “18”.

The graph (2) in the middle of FIG. 6 also shows an example of the ternary average value. However, the ternary average value shown in the graph (2) is shifted to the right by 3 pixels (the number of pixels from the attention pixel 71 to the comparison pixel 72) as compared with the graph (1), that is, in FIG. It represents a ternary average value in a state where the indicated pixel 71 is shifted to the position of the comparison pixel 72.

The graph (3) at the bottom of FIG. 6 shows the absolute value of the value obtained by subtracting the graph (2) from the graph (1) as the streak feature amount. From the graph (3), it is shown that the values with opposite signs (for example, the main scanning position is “18”) are calculated to be larger than the values at other locations. Then, the quality determination unit 613 determines that a streak has occurred at this position if the streak feature amount calculated by taking the difference between the values of the inverse signs is larger than the defect detection threshold value C (for example, “150”). To do.

By the way, in the case of a thin streak having a reading pixel size of the reading unit 45 having a width of only about one pixel, even if the streak can be detected when the streak overlaps the position of one reading pixel, the streak is read when the streak is straddled over two pixels. The concentration drops and cannot be detected. The relationship between such streaks and the reading pixels will be described with reference to FIG. 7.

FIG. 7 is a diagram showing the relationship between the two streaks 70a and 70b and the scanning line 80.
On the left side of FIG. 7, it is shown that two streaks 70a and 70b are generated in the sub-scanning direction of the printed matter 75. Then, the reading unit 45 (see FIG. 2) reads the pixel value of the printed matter 75 in the main scanning direction. The read pixel value is stored for each read pixel of the scanning line 80 parallel to the main scanning direction shown in the figure.

On the right side of FIG. 7, it is shown that the scanning line 80 is composed of a plurality of reading pixels. When the width of each reading pixel in the main scanning direction substantially matches the width of the streak, the streak 70b on the right side coincides with the position of one reading pixel. Therefore, the amount of change in the pixel value due to the generation of the streaks 70b becomes sufficiently large, and the presence of the streaks 70b is detected.

However, in the streak 70a on the left side, the streak 70a straddles the two reading pixels. In this case, the pixel values of the streaks 70a are dispersed among the pixel values read by the two reading pixels. Therefore, the pixel value output by one read pixel corresponding to the streak 70a becomes small, and it is determined as if the streak 70a does not exist.

Therefore, the pixel value stored for each pixel of each reading pixel included in the scanning line 80 is subjected to a predetermined process for each adjacent pixel to extract the streak feature amount.
FIG. 8 is a diagram showing an example of a process of calculating a pixel value stored for each pixel of a scanned image. Here, a state in which one line of read pixels is taken out in the main scanning direction of the read image and the pixel value is calculated is shown.

An example of pixel values stored in the reading pixels of the scanning line 80 is shown on the upper side of FIG.
On the middle side of FIG. 8, the change amount calculation unit 611 calculates the difference between the pixel of interest and the comparison pixel two pixels adjacent to the pixel of interest for the reading pixel of the scanning line 80, and generates a difference image 603c1. It is shown how it is done. The change amount calculation unit 611 refers to the attention pixel 71 when the sign of the difference value calculated for the attention pixel 71 and the difference value calculated for the pixels around the attention pixel 71 match. To the difference value calculated in the above, the difference value calculated for the pixels around the pixel of interest 71 is added, and the difference value is concatenated.

For example, the difference value "-2" from the pixel value "130" of the scanned image on the leftmost side of the scanning line 80 and the pixel value "132" of the comparison pixel two pixels adjacent to each other is the difference value "-2" of the difference image 603c1. It is shown that it is stored at the leftmost pixel position. Similarly, the processing is continuously performed on the other reading pixels, and the difference value of each pixel is stored at the pixel position of the difference image 603c1.

The lower side of FIG. 8 shows a state in which a connected image 81 storing the connected values obtained by calculating the difference values for each pixel before and after the main scanning direction of the difference image 603c1 is generated. Here, the change amount calculation unit 611 performs a process of not adding if the pixel values of the adjacent pixels have different signs, and adding if they have the same sign. For example, the pixel value “-2” of the pixel at the left end of the difference image 603c1 shown in the middle of FIG. 8 and the pixel value “1” of the pixel to the right of this pixel are different symbols.

On the other hand, the pixel value "-10" of the third pixel from the left end of the difference image 603c1 and the pixel value "-11" of the pixel to the right of this pixel have the same code, so that the connected image 81 has the same code. , Concatenated value "-21" is stored. Further, since the pixel value "13" of the fifth pixel from the left end of the difference image 603c1 and the pixel value "10" of the pixel to the right of this pixel have the same reference numerals, the linked image 81 has a linked value. "23" is stored. In this way, the processing is continuously performed on the difference pixels of the other difference images 603c1, and the concatenated value of each pixel is stored in the pixel position of the concatenated image 81.

After the change amount calculation unit 611 generates the connected image 81 in this way, the classification result 603d including the classification value in which each connection value stored in the connection image 81 is classified into three is generated. For example, the change amount calculation unit 611 sets the portion where the pixel value of the connected pixel included in the connected image 81 is larger than the first classification threshold value (for example, “10”) to “255” and the second classification threshold value (for example, “10”). The ternation process is performed so that the portion smaller than -10 ") is set to" 0 "and the portion equal to or more than the second threshold value and equal to or less than the first threshold value is set to" 128 ". After that, the defect feature amount extraction unit 612 extracts the streak feature amount based on the classification result 603d, so that the quality determination unit 613 can detect the occurrence of the streak.

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 the front-back value concatenation process (S3). The front-back value concatenation process will be described later with reference to FIG.

Next, the change amount calculation unit 611 generates a classification result 603d including a value obtained by ternating the connected value of each pixel connected by the front-back value connection process in step S3 with a predetermined threshold value (S4). At this time, the change amount calculation unit 611 digitizes the concatenated value of each pixel with reference to the classification threshold value stored in the parameter 603e. When the concatenated value of each pixel is ternaryized, it is treated as a classification result 603d.

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 (S5), and determines the quality of the read image 603a. In the process of extracting the streak feature amount, as shown in FIG. 6, the defect feature amount extraction unit 612 obtains two types of ternary average values, and one ternary average value is used as the other ternary average value. It is done by reducing the value.

Then, the quality determination unit 613 compares the extracted streak feature amount with the defect detection threshold value read from the parameter 603e, and detects the streak (S6). 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.

FIG. 10 is a flowchart showing an example of the front-back value concatenation process shown in step S3 of FIG.
First, the change amount calculation unit 611 acquires the difference image 603c1 from the RAM 603 (S11). Next, the change amount calculation unit 611 determines whether or not the plurality of pixels in the main scanning direction including the specific pixel in the sub-scanning direction of the difference image 603c1 match the sign of the previous pixel for each pixel of interest. (S12). In this process, the front pixel is, for example, a pixel separated by one pixel on the left side when viewed from the pixel included in the difference image 603c1 shown in the middle of FIG.

Then, if the signs do not match (NO in S12), the change amount calculation unit 611 proceeds to step S14, and if the signs match (YES in S12), the pixel value of the previous pixel is added to the pixel value of the pixel of interest. (S13).

Next, the change amount calculation unit 611 determines whether or not the code of the rear pixel matches the code of the rear pixel for each pixel of interest (S14). In this process, the rear pixel is, for example, a pixel separated by one pixel on the right side when viewed from the pixel included in the difference image 603c1 shown in the middle of FIG.

Then, if the signs do not match (NO in S14), the change amount calculation unit 611 ends this process and returns to step S4 in FIG. On the other hand, if the signs match (YES in S14), the change amount calculation unit 611 adds the pixel value of the rear pixel to the pixel value of the pixel of interest (S15), and returns to step S4 of FIG.

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. Pixel values are concatenated before and after the difference pixel of the difference image 603c1, and after ternation, the streak feature amount is extracted. The inspection processing device 5 detects the streaks in the scanned image 603a based on the extracted streak feature amount. Even if the area where the streaks are generated in the scanned image 603a is flat, the inspection processing device 5 can detect the streaks straddling the width of several adjacent pixels, so that the streak detection accuracy is improved. , The quality of the image formed on the paper Sh is improved.

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 a process for detecting a streak appearing in a previously known flat image region (referred to as a “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 to S13 are the same as the processes of steps S1 to S3 of FIG. Therefore, after explaining the processing after step S21, the processing after step S14 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 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 S13 and S25, the change amount calculation unit 611 performs a quantification process of the connected pixels generated in step S13 based on the threshold image 603f read from the RAM 603, and generates a classification result 603d (S13). .. Next, the defect feature amount extraction unit 612 detects the streak feature amount (for example, FIG. 6) 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, the ternary processing of the connected pixels 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 connected pixels are quantified by the ternary processing and the streak 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.

It should be noted that the present invention is not limited to the above-described embodiment, 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, the above-described embodiment 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 613 ... Image conversion unit, 616 ... Alignment part, 631 ... Streak detection result

Claims (6)

Of the plurality of pixels included in the scanned image read from the recording material on which the image is formed, the pixel value of the pixel of interest and the pixel value of the comparison pixel separated by the first pixel number in the first direction from the pixel of interest. After calculating the difference value with and from each of the attention pixels in the first direction, the difference values separated by the number of second pixels in the first direction are concatenated, and the concatenated value is the classification threshold value. A change amount calculation unit that calculates the classification results classified into a plurality of classification values as the change amount of the pixel value,
Based on the averaging result obtained by averaging the classification value of the classification result in the second direction intersecting the first direction, the feature amount of the streak-like defect generated in the image formed on the recording material. Feature extraction unit to extract
An image inspection apparatus including a quality determination unit that detects a streak-like defect by comparing the feature amount with a preset defect detection threshold value and determines the quality of the image formed on the recording material. When the difference value calculated for the attention pixel and the difference value calculated for the pixels around the attention pixel match, the change amount calculation unit determines the attention pixel. The image inspection apparatus according to claim 1, wherein the difference value calculated for pixels around the pixel of interest is added to the difference value calculated for the above difference value, and the difference value is connected. 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 claim 1 or 2, wherein the change amount calculation unit changes the classification threshold value according to a region in which the pixel value of the read image aligned is changed. The image inspection apparatus according to any one of claims 1 to 3, wherein the change amount calculation unit obtains an averaging result obtained by averaging the classification result in the same direction as the streak-shaped defect to be detected. The image inspection apparatus according to any one of claims 1 to 4, 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 value between the pixel value of the pixel of interest and the pixel value of the comparison pixel separated by the first pixel number in the first direction from the pixel of interest. Is calculated for each pixel of interest in the first direction, then the difference values separated by the number of second pixels in the first direction are concatenated, and the concatenated values are classified into a plurality of classifications by the classification threshold. A change amount calculation unit that calculates the classification result classified into values as the change amount of the pixel value,
Based on the averaging result obtained by averaging the classification value of the classification result in the second direction intersecting the first direction, the feature amount of the streak-like defect generated in the image formed on the recording material. Feature extraction unit to extract
An image inspection system including a quality determination unit that detects a streak-like defect by comparing the feature amount with a preset defect detection threshold value and determines the quality of the image formed on the recording material.

Images