Image thinning and characteristic classification method used for product defect detection and quality control

Abstract

The invention discloses an image thinning and characteristic classification method used for product defect detection and quality control. A pixel of an image is subjected to binaryzation to form a pixel value set area corresponding to the image; end point removal is carried out before an image is skeletonized to eliminate noise influence; an image thinning direction is judged, image skeletonization is carried out, an image is subjected to continuous iteration thinning successively from the upper, lower, left and right pole positions of the image to the inside, and strict image skeletonization is carried out, wherein the strict skeletonization is carried out is characterized in that continuous iteration thinning is carried out successively from the north, the south, the west and the east points of the image. When the image is not thinned or reaches thinning frequencies, redundant end points are removed, and the image is smoothly processed. A round area forms a point after being thinned, and a skeleton keeps original information; the method consumes time like a Davies two-step method; and after an END point is defined, end point interference can be eliminated, and an improved thinning principle is cooperated to guarantee judgment validity.

Description

technical field

[0001] The invention relates to the field of image detection, in particular to defect detection and product quality control methods for products such as electronics, printing, and glass panels. Background technique

[0002] With the development of large-scale industrial production, people have higher and higher requirements for product quality control. The traditional way of using human eyes to detect products is far from meeting the needs of modern industrial production. It is the trend of the times to carry out defect detection and quality control of products. Image thinning technology, that is, skeletonization, is to reduce the binary image to a series of lines with a single pixel, eliminate a large amount of redundant information in the image, and accurately retain the original image information. In the defect detection of array graphics such as plasma panel printing graphics, For defects such as disconnection and burrs, it can be detected efficiently an...

Examples

Embodiment Construction

[0050] The present invention will be further described below in conjunction with accompanying drawing:

[0051] The directional terms mentioned in the following embodiments, such as "up, down, left, right" are only referring to the directions of the drawings, therefore, the directional terms are used for illustration and not for limiting the present invention.

[0052] This method is an improved method by improving the four-step method of Dayies. The general four-step method of Dayies is first introduced below. This method continuously iterates and thins the image in four steps from top, bottom, left and right: 1. It introduces the concept of crossover number χ (combined with Figure 4 ):

[0053] χ=(b 2 ! =b 4 )+(b 4 ! =b 8 )+(b 8 ! =b 6 )+(b 6 ! =b 2 )+2*((~b 2 &b 1 &~b 4 )+(~b 2 &b 3 &~b 6 )+(~b 4 &b 7 &~b 8 )+(~b 8 &b 9 &~b6 ))

[0054] 2. Neighborhood sum: σ=b1+b2+b3+b4+b6+b7+b8+b9

[0055] 3. Define north, south, east, west points, take the nort...

technical field

[0001] The invention relates to the field of image detection, in particular to defect detection and product quality control methods for products such as electronics, printing, and glass panels. Background technique

[0002] With the development of large-scale industrial production, people have higher and higher requirements for product quality control. The traditional way of using human eyes to detect products is far from meeting the needs of modern industrial production. It is the trend of the times to carry out defect detection and quality control of products. Image thinning technology, that is, skeletonization, is to reduce the binary image to a series of lines with a single pixel, eliminate a large amount of redundant information in the image, and accurately retain the original image information. In the defect detection of array graphics such as plasma panel printing graphics, For defects such as disconnection and burrs, it can be detected efficiently an...

Examples

Embodiment Construction

[0050] The present invention will be further described below in conjunction with accompanying drawing:

[0051] The directional terms mentioned in the following embodiments, such as "up, down, left, right" are only referring to the directions of the drawings, therefore, the directional terms are used for illustration and not for limiting the present invention.

[0052] This method is an improved method by improving the four-step method of Dayies. The general four-step method of Dayies is first introduced below. This method continuously iterates and thins the image in four steps from top, bottom, left and right: 1. It introduces the concept of crossover number χ (combined with Figure 4 ):

[0053] χ=(b 2 ! =b 4 )+(b 4 ! =b 8 )+(b 8 ! =b 6 )+(b 6 ! =b 2 )+2*((~b 2 &b 1 &~b 4 )+(~b 2 &b 3 &~b 6 )+(~b 4 &b 7 &~b 8 )+(~b 8 &b 9 &~b6 ))

[0054] 2. Neighborhood sum: σ=b1+b2+b3+b4+b6+b7+b8+b9

[0055] 3. Define north, south, east, west points, take the nort...

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