基于学习的 Gabor 滤波器多样式布匹瑕疵检测.

Cloth patterns and complex pattern make difficult to detect defects in the manufacturing process. Thus,a learning-based Gabor filter in multi-style fabric defect detection is proposed. First, Gabor filters are used to filter multi-style cloth at different directions and scales and select the optimal filter scale. Then, the defect features are extracted by using digital image feature discriminant,the feature images are segmented, and a number of preferred feature information blocks are merged. Finally, the fused images are processed by binarized and morphological filtering. Experimental results show that the method performs effectively both in flaw detecting of multi-style cloth and in real-time performing. Compared with similar algorithms, the detection accuracy and time efficiency have a certain increase. [ABSTRACT FROM AUTHOR]