Abstract
This article discusses the issue of express evaluation of the presence of a defect on the surface of a galvanized strip. A review of the most common defects in the production of galvanized metal products, including roughness and seam, has been made. To determine the defect, image pre-processing is used - noise removal using Gaussian blur. After pre-processing of the adaptive thresholding algorithm by the 1D kernel in two directions. As a result, it was concluded that this method is not sensitive to image noise resulting from a communication channel failure, video sensor noise, or camera defect. This algorithm can be used both independently and as part of a more complex algorithm, which involves not only the determination of strip surface defects, but also the subsequent classification.
Keywords
surface inspection of galvanized steel, defect recognition, defect detection, defect classification, automated surface inspection systems, surface inspection, machine vision, computer vision.
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Garbar E.A. and Nikolaev A.A. (2020) Express evaluation of galvanized rolled steels surface defect. Software of systems in the in- dustrial and social fields. 8 (1): 23-30. DOI: 10.18503/2306-2053-2020-8-1-23-30.