关键词: 皮革缺陷检测, 光度立体视觉, 曲率滤波, 显著性目标检测, 图像分割

Abstract: To improve the efficiency of leather defect detection, a leather defect detection algorithm is proposed by combining photometric stereo with saliency object detection. First, a acquisition platform for photometric stereo is established to collect leather samples in different orientation. Then, photometric stereo is applied to obtain a synthetic image and a surface normal vector image. Next, the surface normal vector image is processed by curvature filtering and the synthetic image or the filtered image is selected by the approximate surface roughness features. Finally, defect detection is performed based on saliency object detection. Experimental results indicate that, compared to the existing methods, the proposed algorithm can detect several kinds of defects on different leathers made of different materials at a high accuracy and a high speed.

Key words: leather defect detection, photometric stereo, curvature filtering, saliency object detection, image segmentation