Supervised defect detection on textile fabrics via optimal Gabor filter

Abstract

An effective defect detection scheme for textile fabrics is designed in this article. Interestingly, this approach is particularly useful for patterned fabric. In the proposed method, firstly, Gabor filter is adjusted to match with the texture information of non-defective fabric image via genetic algorithm. Secondly, adjusted optimal Gabor filter is used for detecting defects on defective fabric images and defective fabric images to be detected have the same texture background with corresponding defect-free fabric images. The significance of the proposed approach lies in selecting Gabor filter parameters with an abundance of choices to build the optimal Gabor filter by means of genetic algorithm and achieving accurate defect detection on patterned fabric. High success rate and accuracy with little computational time online are obtained in the defect detection on fabrics, which indicate that the suggested method can be put to use in practice.