The design of optimal real Gabor filters and their applications in fabric defect detection

Abstract

Fabric defect detection has been recognised as one of the key challenges for automatic production, and Gabor filters are one of the most useful tools in detecting fabric defects. The half‐peak tangent method is applied in real Gabor filter design so that the filters can cover the frequency of defects as much as possible. Meanwhile, the half‐peak‐magnitude contours of the neighbouring filters are tangential. On this basis, two optimal orientations are selected by applying direction masks, and the optimal scale at each optimal orientation is determined according to the signal‐to‐noise ratio. In this way, two optimal real Gabor filters are obtained. A new algorithm based on the two optimal filters is proposed for fabric defect detection. A series of experiments are carried out for 46 fabric defect images combined with 46 corresponding reference fabric images, in order to verify the effectiveness of the new algorithm. The experimental results obtained show that the new algorithm can accurately detect defects in grey fabric defect images as well as in colour images. For the 46 fabric defect images, the detection rate is 95.66%, indicating that the new algorithm performs well. In addition, comparison of the new algorithm with other algorithms in the literature demonstrates that the new algorithm is more effective in the detection of several fabric defect images.