摩擦片表面缺陷的视觉显著性检测算法

A detection algorithm based on visual salience was proposed according to the requirement of high precision and efficiency for detecting the surface defect of friction sheet and complex surface conditions of the friction sheets themselves. The friction sheets were separated from background by the image segmentation. The surface texture was smoothed by Gaussian Blur. The multi-scale detail enhancement algorithm was used to compensate missing defect edge information in Gaussian Blur, and the saliency of the target in this image was calculated for differentiation. The connected domain method and Otsu were utilized to extract the binary images of the defect area. The experimental results show that the algorithm has strong pertinence for the defect detection of friction sheets. The defect recognition rate is over 98%. It takes 27 s to detect 100 friction sheets on both sides. From objective and subjective aspects, the detection results prove that the algorithm has high recognition rate and accuracy to meet the demand of industrial assembly.