A method for image extraction of steel plate surface defects

Abstract

The invention provides a steel plate surface defect image extraction method. The method is characterized by including the following steps that steel plate surface images are subjected to ROI detection, and non-defect images are removed; defect images are sequentially read, the images are preprocessed, the influences of noise and non-uniform illumination on the defect segmentation effect are removed, and the foreground and background contrast ratio is increased; the preprocessed steel plate defect images are subjected to defect region segmentation extraction through Center-Surround Difference, and finally data is output. The efficiency of an image extraction algorithm is improved, it is not needed to occupy large memory space, real-time processing is convenient, the influence of the noise is effectively weakened, wrong extraction, caused by illumination and brightness unevenness, of the images is avoided, the contrast ratio is increased, the defect extraction effect is more excellent, and details are complete.

Description

Technical field [0001] The invention relates to the technical field of machine vision and nondestructive testing, and in particular to a method for extracting defects on the surface of a steel plate under the interference of multiple defects. Background technique [0002] Steel products are widely used in construction, home appliances, vehicles and ships, container manufacturing, electrical and mechanical industries, etc., and almost involve all areas of clothing, food, housing and transportation. During the production and processing of steel plates, it is susceptible to the influence of many factors such as raw materials, rolling equipment, and worker operation techniques, which can lead to the occurrence of various defects such as holes, scratches, inclusions, scratches, and roll marks. The existence of these defects affects the appearance of the steel plate, but also affects its corrosion resistance, wear resistance and fatigue strength, which seriously reduces the quality of ...

AI Technical Summary

Problems solved by technology

[0007] In the extraction process, there will be the following problems, such as the influence of the lighting environment and the difference in the light absorption and reflection of the steel plate itself, resulting in uneven illumination of some steel plate images, loss of some useful information, low contrast between the front and back, and increasing the difficulty of defect target extraction. ; or the collected image is easily affected by the background environment, such as noise, texture and other factors, the image quality is low, the edge is not clear, and the target area is difficult to extract; moreover, there are many types of defects, different shapes, different degrees of severity, The contrast between the foreground and background of some defect images is still low after image enhancement, these factors increase the difficulty of defect extraction

These problems seriously reduce the efficiency and accuracy of defect area extraction, which affects subsequent defect identification

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