JPH07186375A - Inspection method for printed matter - Google Patents

Abstract

PURPOSE:To obtain an inspection method for a printed matter by which the defect of the printed matter can be correctly detected in an in-line system, and the edge part that has been an uninspectable area in a prior art can be inspected. CONSTITUTION:Image pattern information of a printed matter fed from a printing part 1 is received by a detection part 4 per pixel in accordance with a sampling timing obtained from a rotary encoder 5 to be inputted to a processing circuit 6. The processing circuit 6 receives image pattern information of a normal printed matter, forms an image thereform, and filters it through a minimum value filter and/or a maximum value filter to form a reference image. A difference value is found by comparing this image with an image to be inspected. A defect is detected by comparing the difference value with an allowable value (a threshold).

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for inspecting a printed matter by detecting the abnormality of the printed matter by in-line comparing the state of the printed matter during printing with a reference material.

[0002]

2. Description of the Related Art Conventionally, the mainstream of the inspection of printed matter has been off-line and relying on human vision. This is because the determination of normality / abnormality in the printed matter is made by a subtle difference that must rely on human vision. On the other hand, a means for capturing a picture of a printed matter as a still image by a mirror that rotates at high speed in synchronization with the printed matter being printed and a means for improving inspection accuracy by stroboscopic illumination synchronized with the printing speed have been adopted. However, these are all methods of inspecting by human vision. On the other hand, recently, a system for in-line inspection of a printed matter using a line sensor has been adopted. This system takes in the picture information of the printed matter for each pixel and compares this image with the reference image for each pixel to detect an abnormality that occurred during printing.

[0003]

The printed matter slightly meanders or expands or contracts even when printed in a normal operation. Therefore, if the reference image and the captured image are simply compared on a pixel-by-pixel basis, a significant difference occurs at the edge portion of the pattern, and a problem arises in that a normal printed matter is erroneously determined to be abnormal. Various methods have been studied in the field of image processing for accurate alignment, but in the case of pattern inspection of printed matter, the inspection target is large, it is necessary to make the resolution fine, and the amount of data is enormous and the printing speed is also high. Due to the high speed, it is practically impossible to inspect the edge portion after performing accurate alignment. Therefore, in the conventional method, the edge portion is masked to form a non-inspection area. The mask portion extracts the edge portion by edge detection processing such as differentiation and a Sober filter and binarizes it to use as a binary mask. As described above, in the conventional technique, the edge portion is masked as a non-inspection area, and therefore, there is a problem that even if an abnormality occurs in this area, it is not detected.

The present invention was devised in view of the above circumstances, and an inspection of a printed matter can be performed accurately in-line, and an inspection of an edge region which has been difficult in the prior art can be performed. The purpose is to provide a method.

[0005]

In order to achieve the above object, the present invention is based on an image obtained by applying a minimum value filter and / or a maximum value filter to an image in which picture information of a normal print is taken in for each pixel. As an image, an image in which the picture information of the printed matter of the inspection object is captured for each pixel is used as an inspection image, a difference value between the inspection image and the reference image is calculated, and the difference value is compared with an allowable value to determine an abnormality. It is characterized by a method of inspecting a printed matter for detecting the presence or absence of Here, the minimum value filter or the maximum value filter is a filter that performs a process of setting a minimum value or a maximum value in n × m pixels in the vicinity of the target image as a new value of the target pixel.

[0006]

The pattern information of a normal printed matter is fetched for each pixel by a line scanner or the like, and the reference image is created by performing a filtering process by the minimum value filter and / or the maximum value filter. On the other hand, the picture information of the printed matter to be inspected is taken in for each pixel and used as an inspection image. All the pixels of this inspection image and the reference image are compared to obtain the difference value. This difference value is compared with a predetermined allowable value, and when the difference value exceeds the allowable value, it is determined that the printed pattern is abnormal, and the printed matter is determined to be abnormal. The above image processing is automatically performed inline.

[0007]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a layout diagram showing a schematic configuration of the present embodiment, FIGS. 2 to 9 are explanatory views for explaining the contents of reference images and inspection images and the inspection method of this embodiment, and FIG. 10 is for explaining an edge portion inspection method. FIG. 11 is a pixel gradation value-frequency diagram for explaining the edge inspection method, and FIG. 12 is a block diagram of the processing circuit of this embodiment.

First, an outline of this embodiment and a printing apparatus to which it is applied will be described with reference to FIG. Although the inspection apparatus of this embodiment is attached to a rotary press in the figure, any machine such as a sheet-fed printing machine or a rewinding inspection machine having a mechanism for conveying sheets at a constant speed may be applied. The strip-shaped printing paper 3 supplied from the roll-shaped winding web 2 is printed by the printing unit 1 in each color. The inspection device is installed after the final color printing unit in order to inspect the printing state after all colors are printed. The rotary encoder 5 attached to one of the rollers of the printing unit 1 takes sampling timing and inputs it to the processing circuit 6. The detection unit 4 reads the pattern of the printed matter on the printing paper 3, and is arranged so as to face the printing paper 3.
The pattern information is printed on the printing paper 3 by the line sensor of the detection unit 4.
The reading is performed by scanning in the direction orthogonal to the flow direction of.
That is, the scanning of the line sensor is the main scanning, the flow of the printing paper 3 is the sub-scanning, and the design of the printed matter is taken into the processing circuit 6 pixel by pixel. As will be described later in detail, the processing circuit 6 determines whether the printed matter is normal or abnormal. If the judgment result is abnormal, it is dealt with by means such as alarm, marking, and reject.

The processing circuit 6 is, as shown in FIG. 12, a timing controller 7 connected to a rotary encoder 5.
And A / D that is connected to the detection unit 4 and A / D exchanges detection signals.
D converter 8, inspection image storage memory 9 for storing inspection images, and minimum value image storage memory 1 for storing reference images
0 and maximum value image storage memory 11 and minimum value filter circuit 12 and maximum value storage filter circuit 13 for creating minimum value and maximum value image storage memories 10 and 11.
And a difference circuit 14 for obtaining a difference value between the inspection image and the reference image.
And defect candidate image storage memories 15 and 16 for storing the defect candidate image subjected to the difference processing, and a predetermined allowable value (threshold value)
A binarization circuit 17, which binarizes the defect candidate image by
18 and a defect image storage memory 19 for storing a defect candidate image having a difference value exceeding an allowable value as an abnormal image.

Next, the inspection method of this embodiment will be described. A shown in FIG. 2 is a normal printed matter (hereinafter referred to as a printed matter A), and a printed matter B is a printed matter having a print defect. It should be noted that the defect 20 of the printed matter B is caused by adhesion of dust, ink, etc., and the defect 21 is a pinhole-like defect in which ink is not partially adhered. It should be noted that if the gradation value of a pixel is small in the dark portion and large in the bright portion, the gradation value of the defect 20 is small and the gradation value of the defect 21 is large. An image in which the picture information of the printed material A is captured for each pixel is referred to as an image C and is shown in FIG. On the other hand, an image in which the picture information of the printed matter B is taken in for each pixel is referred to as an image F and is shown in FIG. This image F corresponds to the inspection image. An image obtained by applying the minimum value filter to the image C is shown as an image D in FIG. This image D becomes the first reference image. On the other hand, an image obtained by applying the maximum value filter to the image C is shown as an image E in FIG. This image E
Is the second reference image.

Next, a specific method of filtering by the minimum value filter and the maximum value filter will be described. The minimum value filter sets each pixel of the image C as a target pixel, selects n × m pixels in the vicinity of the target pixel, obtains the smallest gradation value within the frame, and sets the value as the gradation value of the target pixel. The processing to be performed is sequentially performed. On the other hand, the maximum value filter sets each pixel of the image C as a target pixel, selects n × m pixels in the vicinity of the target pixel, obtains the largest gradation value within the frame, and determines the value as the gradation of the target pixel. It is a process that takes a value. Note that n and m are determined in consideration of the meandering amount of paper, the amount of expansion and contraction, the degree of image blurring, etc., and are set appropriately.

Next, the first and second reference images (image D
A method of detecting a defect in the image F, which is the inspection image, using the image and the image E) will be described. The inspection method compares the reference image and the inspection image for each pixel to obtain the difference value. First, the difference in gradation value of each pixel of the image F is obtained from the image D, and when the difference value is negative, it is replaced with 0. The result is shown in image G of FIG. The above processing is expressed by the FIX function of the following equation. G = FIX (DF) Since the gradation value of each pixel of the image D is replaced with a smaller value than the gradation value of the original image C by the minimum value filter processing, the image F has no replacement of the gradation values. The gradation value of most pixels is larger in the image F than in the image D. Therefore, the value of DF becomes almost negative or zero. When the difference value is negative or zero, the gradation value of the pixel is set to zero. However, image F
Among them, the defect 20 is a dark image due to dust, ink, etc., and the gradation value is small. Therefore, only for the defect 20, the value of DF becomes a positive value and becomes a positive difference value. Therefore, by G = FIX (DF), the image G in FIG.
As shown in, the defect 20 is highlighted as a defect candidate. This defect candidate is compared with a predetermined allowable value (threshold value), and if the difference value is larger than the allowable value, it is determined to be a defect. Image E and image F are compared by the same method as described above and H
= FIX (FE) is calculated. The image E is made by replacing the gradation values of all the pixels of the original image C with large values by the maximum value filter processing, and FE becomes minus or zero in most of the pixels. However, the portion corresponding to the defect 21 has a large gradation value, FE becomes positive, and a positive difference value is obtained. Therefore, as shown in FIG. 9, the defect 21 is highlighted as a defect candidate in the image H. This defect candidate is compared with a predetermined allowable value (threshold value), and if the difference value is larger than the allowable value, it is determined to be a defect. As described above, the defects 20 and 21 of the printed matter B can be detected.

FIG. 12 shows a processing circuit 6 which can be executed by this embodiment.
The block diagram of is shown. The operation of the inspection apparatus shown in FIG. 1 will be described with reference to this. The timing control unit 7 gives a sampling start signal or the like to the detection unit 4 based on the timing pulse generated by the rotary encoder 5 attached to the plate cylinder or the impression cylinder of the printing unit 1. Detection unit 4
The video signal output from the storage unit 9 is stored in the inspection image storage memory 9 via the A / D converter 8. Further, when the reference image is produced, it is stored in the minimum value image storage memory 10 and the maximum value image storage memory 11 via the minimum value filter circuit 12 and the maximum value filter circuit 13, respectively. The inspection image storage memory 9 and the minimum value image storage memory 10 are subjected to difference calculation by the difference circuit 14 for each pixel, and the defect candidate image storage memory 1
Stored in 5. Similarly, the maximum value image storage memory and the inspection image storage memory 9 are also subtracted and stored in the defect candidate image storage memory 16. Each defect candidate image is a binarization circuit 17,
After being binarized at 18, it is stored in the defect image storage memory 19.

Next, the defect detection in the edge portion will be described with reference to FIGS. As shown in FIG. 10, this printed matter has a gradation value of X range of about 130,
It is assumed that the range of Y has a gradation value of about 80. X and Y
The histogram of MAX and MIN in FIG. 11 shows the gradation value distribution obtained by applying the above-mentioned minimum value filter and maximum value filter to the pixels near the edge portion 22 of the boundary of the above. It is assumed that the defect R and the defect S shown in FIG. 11 occur near the edge portion 22. Defect R is 4
The gradation value is 0, and the defect S has a gradation value of 100. First, the FIX function of the defect R is obtained using the same detection method as described above. FIX (40-130) → minus → 0 FIX (80-40) = 40 Therefore, since the positive difference value 40 is obtained, the defect R is detected by the first reference image subjected to the minimum value filter. Next, the FIX function of the defect S is obtained. FIX (100-130) → minus → 0 FIX (80-100) → minus → 0 Due to the above, the defect S cannot be obtained. From the above,
The inspection method according to the present embodiment cannot detect a halftone defect of a light portion and a dark portion in the edge portion, but the other edge portions 22.
It can be seen that the defect of 1 is detectable. Originally, halftone defects are rare and unnoticeable. For this reason, the inspection method of the present embodiment is superior to the prior art in the edge detection function.

[0015]

According to the present invention, the following remarkable effects are obtained. 1) It is possible to inspect the edge portion, which was conventionally a non-inspection area, and most defects in the edge portion are detected. 2) Defects in printed matter are accurately and automatically detected in-line. 3) Highly accurate measurement is performed by appropriately setting the allowable value and the value of n × m according to the picture state of the printed matter.

[Brief description of drawings]

FIG. 1 is a configuration diagram showing a schematic structure of an embodiment of the present invention and a printing apparatus to which the embodiment is applied.

FIG. 2 is a plan view showing a normal printed material A. FIG.

FIG. 3 is a plan view showing an inspection printed matter B having a defect.

FIG. 4 is a plan view showing an image C in which a printed matter A is captured.

FIG. 5 is a plan view showing an image D obtained by applying a minimum value filter to the image C.

FIG. 6 is a plan view showing an image E obtained by applying a maximum value filter to the image C.

FIG. 7 is a plan view showing an image F in which a printed matter B is captured.

FIG. 8 is a plan view showing an image G formed by obtaining a difference between the image F and the image D.

FIG. 9 is a plan view showing an image H formed by obtaining a difference between the image F and the image E.

FIG. 10 is a plan view showing a printed material sample for explaining defect detection of an edge portion.

11 is a gradation value-frequency diagram obtained by filtering the printed material sample shown in FIG.

FIG. 12 is a block diagram of a processing circuit capable of executing this embodiment.

[Explanation of symbols]

 1 Printing Section 2 Winding Web 3 Printing Paper 4 Detection Section 5 Rotary Encoder 6 Processing Circuit 7 Timing Controller 8 A / D Converter 9 Inspection Image Storage Memory 10 Minimum Value Image Storage Memory 11 Maximum Value Image Storage Memory 12 Minimum Value Filter Circuit 13 Maximum value filter circuit 14 Difference circuit 15 Defect candidate image storage memory 16 Defect candidate image storage memory 17 Binarization circuit 18 Binarization circuit 19 Defect image storage memory 20 Defect 21 Defect 22 Edge part

Front page continued (72) Inventor Ryohei Kumagai 3-5-18 Kitazawa, Setagaya-ku, Tokyo Easel Co., Ltd.

Claims (3)

[Claims] 1. An image obtained by applying a minimum value filter to an image in which the picture information of a normal printed matter is captured for each pixel is used as a reference image, and an image in which the picture information of the printed matter of the inspection object is captured is used as an inspection image, An inspection method for calculating a difference value between the inspection image and the reference image, and comparing the difference value with an allowable value to detect the presence / absence of an abnormality, wherein the minimum value filter includes a neighborhood n × of a target pixel. A method for inspecting a printed matter, which is a filter for performing processing for setting a minimum value of m pixels as a new value of the pixel of interest. 2. An image obtained by applying a maximum value filter to an image in which the picture information of the normal printed matter is captured for each pixel is used as a reference image, and an image in which the picture information of the printed matter of the inspection object is captured is used as an inspection image, An inspection method for calculating a difference value between the inspection image and the reference image and comparing the difference value with an allowable value to detect the presence / absence of an abnormality, wherein the maximum value filter includes a neighborhood n × of a target pixel. A method for inspecting a printed matter, which is a filter for performing processing for setting a maximum value in m pixels as a new value of the pixel of interest. 3. The reference image to which the minimum value filter has been applied is a first reference image, the reference image to which the maximum value filter has been applied is a second reference image, the inspection image and the first and second reference images. 3. The method for inspecting a printed matter according to claim 1, wherein a difference value with respect to the image is calculated, and the difference value is compared with an allowable value to detect the presence or absence of abnormality.