Abstract:

A fabric weaving defect detection algorithm based on dynamic fuzzy clustering is proposed to solve problems such as poor adaptability and real-time in fabric defect detection algorithms. The gray average projection in the weft and warp direction is regarded as eigenvalue after images preprocessing. The suspicious defect region is separated with dynamic fuzzy clustering algorithm according to the projection distortion on the gray average in defect region, which is located and extracted from suspicious defect region by selecting proper thresholds of the distortion density and degree so that the pseudo defect region is filtered out effectively. The results of experiments show that this algorithm has the features of high reliability, strong adaptability and anti-noise-interference ability.