Fast Surface Defect Detection Using Improved Gabor Filters

Surface inspection and defect detection are essential procedures in the quality control of mass production. It is challenging to identify curvilinear defects on a complex background. This paper proposes a novel and fast surface defect detection method based on improved Gabor filters. The introduced system firstly employs improved Gabor filter banks to generate corresponding energy maps. Hysteresis thresholding combined with region grouping and pruning is used to extract defect regions, integrate defect fragments and remove false positives. Our method exhibits excellent performance on two different kinds of surface defect dataset and thus proves to be a practical and accurate solution to surface defect detection.