Abstract:

Because of the variety of fabric texture and the uncertainty of the shape and size of defects, the existing fabric defect detection methods based on image processing are low in accuracy. In order to solve this problem, a new method of fabric defect detection based on structure-texture model and the adaptive mathematical morphology was designed. The fabric texture was firstly filtered based on the relative total variation model, then, the gray morphological operation based on adaptive neighborhood was directly performed on the gray level image, which is morphological operatio, finally the enhanced image of fabric defects was obtained. The algorithm based on the relative total variation model and the adaptive mathematical morphology as well as the other two known algorithms based on Gabor filter was carried out on 4 types of fabric defects with high frequency, and the results show that the method can more effectively extract the fabric defects.

Key words: fabric defect, structure-texture model, relative total variation model, mathematical morphology, adaptive neighborhood