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The paper deals with computer vision and image processing methods applied to the task of corrosion damage search. A step-by-step algorithm is given for processing of the data from a chemical corrosion experiment on a metal surface: image preprocessing, image binarization and identification of object contours, and analysis of object characteristics. The application of the developed methods is exemplified by detection and recognition of corrosion damage on a steel specimen, pitting corrosion, and corrosion of an aluminum specimen. Furthermore, the mechanism of fractal analysis for corrosion cracking specimens was studied and fractal dimension was selected as characteristics of corrosion damage.
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Enikeev et al. (2017) studied this question.
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