关键词: 带钢边部, 孔洞缺陷, 图像处理, 质量控制

Abstract: In order to detect hole defects on cold rolled steel strip edge, a novel detection method combining on-line inspection and off-line extraction of defect details is proposed. An adaptive region growing method is proposed for image segmentation in on-line module. Morphological processing and optimal entropy method are combined to find out seed points, which can overcome the shortage of selecting seed points by manual in traditional method, and the area of the largest component in the result of region growing is employed to judge whether hole defects exist. For making sure the accuracy of detection, block projection histogram matching features and Tamura texture are individually used to extract defect information in off-line module. Defect details can be obtained by integrating two detection results. Multiple images are processed by the algorithm proposed, and experimental results show that the on-line part has high processing speed and discrimination rate. From the off-line part, the number, area and location of holes can be obtained. The speed and precision meet the practical requirements.

Key words: strip edge, hole defect, image processing, quality control