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Singular value decomposition for texture defect detection in visual inspection systems

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2 Author(s)
Tomczak, L. ; Dept. of Comput. Eng., Lodz Tech. Univ., Stefanowskiego ; Mosorov, V.

In this paper the authors propose an algorithm for texture defects detection, which doesn't use supervised classification. The algorithm can be simply applied in an automatic visual inspection system. For localization of texture defects features calculation of each non-overlapping region of an image via the singular value decomposition (SVD) and image processing techniques. In next step the algorithm uses the fuzzy c-means clustering (FCM) to classify each region into two clusters. Finally the authors define a distance between centres of defective and non-defective clusters using some threshold value chosen empirically

Published in:

Perspective Technologies and Methods in MEMS Design, 2006. MEMSTECH 2006. Proceedings of the 2nd International Conference on

Date of Conference:

May 2006