关键词: 布匹瑕疵检测, Gabor优化选择, 代价函数

Abstract: Fabric defect detection based on traditional optimal Gabor filter has the drawbacks of low accuracy and poor robustness. An improved selection method is proposed to choose the optimal Gabor filter. The method is based on a cost function which is the sum of squared mean difference of each blocks indefect image and standard image. A group of Gabor filters are selected and the relevant parameters are figured out from standard images. The improved selection method is used to choose the optimal filtered image. The optimal filtered image is segmented with iterative threshold segmentation. According to the pixel information of the segmented image, it is detected whether the defect is included and the defect information is output. The method is validated by experiments. Compared with the traditional optimization selection method, the results show that the method has less computational complexity and high inspection performance, which can meet the requirements of online detection.

Key words: fabric defect detection, optimal Gabor filter, cost function