Product edge defect detection method

Abstract

The invention discloses a product edge defect detection method. The method comprises the following steps: step 1, carrying out image input; step 2, carrying out image preprocessing; step 3, carrying out template rough matching; step 4, segmenting edge information to be measured; step 5, creating a template data structure; step 6, down-sampling the edge information to be measured; step 7, carryingout matching in the template; step 8, calculating affine transformation parameters; step 9, carrying out template fine matching; and step 10, carrying out edge defect detection. According to the method, the edge information of the image is binarized, so that the method has the advantages of being insensitive to illumination change and edge gray scale and being stable and reliable; the edge information downsampling is utilized to iterate template matching parameters from coarse to fine, so that the method has the advantage of high calculation speed; the RANSAC principle and the fine matching mode of parameter iterative optimization are utilized, so that the method has the advantage of high detection precision; and a segmented matching template matching mode is adopted, so that the advantageof stretching resistance is achieved.

Description

technical field [0001] The invention relates to a defect detection method for cover plates and plate products, in particular to a rapid stretch-resistant edge defect detection method. Background technique [0002] Industrial products often contain edges of various shapes, such as edges of circles, rectangles, and combinations of straight lines and arcs. Edge is an important feature of industrial products, which directly affects the quality of industrial products, and the defects on the edge of general products are mostly serious defects of products, such as bud missing, sawtooth, chipping and other defects directly lead to product scrapping. Product edge defect detection is an important step to ensure product quality. [0003] Edge defect detection mainly detects the consistency of the edge of industrial products, that is, detects whether there are defects such as convex marks and dents on the edge of industrial products. Specifically, for example, the edge defect detectio...

AI Technical Summary

Problems solved by technology

The research on edge defect detection algorithms at home and abroad is not very versatile. One type of algorithm uses straight line fitting to compare the distance from the edge point to the fitted line to detect edge defects in straight line areas; the other type of algorithm uses open and close operations to compare The change of the area detects the edge defects of the complete area with smooth edges; there is another type of algorithm that uses template matching to compare the similarities and differences between the test and the template to detect the edge defects of the target image

[0007] However, the above methods are not suitable for defect detection of stretched edges

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