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A surface defect detection method based on multi-features is proposed for the detection of complex ceramic disc surface. Firstly, geometric transformation is implemented on the image being detected, which makes the direction and position of the image to be unified. Then, according to the standard template, the image is separated into several regions with different gray characteristics for interval inspect. Defects containing broken, chipping, uneven polishing, crack, etc. are classified into two types—blob defect and crack defect. Blob defect detection is mainly based on the analysis of the abnormal part of regional gray value, and the crack detection is based on the analysis of shape and neighborhood gray gradient changes. Experimental result shows that the algorithm proposed is sensitive to the surface defects, and can effectively reduce the false positives with detection rate more than 94%, detection speed up to 5 parts per second.
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