A New Multi-Scale/Multi-Directional Method for Detection of Abnormalities in Random Textures

A. Monadjemi (Iran)


: Machine Vision, Texture, Abnormality Detection, MSMD Methods.


This paper proposes a new Gabor filter-based generative approach to texture abnormality detection, called Gabor Composition or GC. The GC algorithm, a combination of Gabor filtering and co-occurrence analysis, employs a Gabor filter bank to generate a multi-scale and multi directional feature map of the test image. The feature map is then fed to a co-occurrence based feature extraction mod ule, which is able to extract more efficient textural fea tures from the conditioned signal. A comparative defect detection test applied on a database of randomly textured ceramic tiles, illustrates the advantages of the proposed method.

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