The Algorithm Research Of Steel Surface Defect Inspecting System Based On Machine Vision

In order to satisfying customer requirements of continually raise the speed and efficiency of steel production. The automatic inspecting technology about surface defect of steel production becomes more and more important. Traditional surface defects inspection done by human inspectors is far from satisfactory, for its labor-intensive and high rate of false detection. With the development of computer capacity, automatic strip surface inspection based on image has become favorable question for study.Researching on scratch on the surface of steel production, this paper researches the key techniques of the inspection system. The general design scheme of surface defects inspection system for hot rolled steel plate is given, hardware and software of the system is described, and algorithms for image noise removing, image enhancement and region segmentation are discussed.The main work included in the dissertation is shown as follows:1.According to inspection system's technical requirement, its overall design plan is put forward. It include hardware and software design scheme.2.Putting forward the method for the acquirement the noisy image, finding the noisy character and advancing the combinatorial optimization filter.3.According to the surface defect characteristics of scratch, the conventional defect processing algorithms of gray-scale enhancement, segmentation are studied in-depth, and on this basis, inspecting algorithm which adapting to this system is designed out, and simulated on MATLAB.This thesis studies the image processing in steel surface inspection fields. Experiments show that the proposed algorithms to highlight surface defects are effective.