We propose a unified framework for detecting defects in planar industrial products or planar surfaces of nonplanar products based on a template-matching strategy. The framework includes three parts: an automatic selection of template image for a given test one, a robust geometric alignment between template and test images based on an approximate maximum clique approach, and an illumination invariant image comparison method for defect detection in the aligned images. Experimental results on challenging image datasets demonstrate the excellent performance of the proposed framework.
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Kong et al. (2017) studied this question.
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