Texture crack detection |
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Authors: | Keng Yew Song Maria Petrou Josef Kittler |
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Affiliation: | (1) University of Surrey Vision, Speech and Signal-Processing Research Group, Department of Electronic and Electrical Engineering, GU2 5 XH Guildford, UK |
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Abstract: | Automatic visual inspection has become one of the active research issues in machine vision technology in the past decades. Most of the methodologies developed address the problems of defect detection on a nontextured or regularly textured surface. However, problems in detecting defects on a randomly textured surface, especially cracks, have not received much attention. In this paper, we present a novel algorithm that uses a Wigner model to identify cracks in complex textural backgrounds, regardless of whether the inspected surface is randomly or regularly textured. We also investigate the windowing characteristics of the Wigner distribution and their impact on crack detection. Some of the Brodatz' natural texture images have been used for evaluating the performance of the algorithm. Promising results are obtained and presented in this paper. |
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Keywords: | Texture analysis Crack detection Wigner distribution Surface inspection |
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