Abstract: To improve the recycling rate of waste circuit boards,aiming at the common defects on the surface of recycled circuit boards,a quadtree split color histogram detection method was proposed based on uniform blocking,the surface defects of circuit boards were located effectively and quickly,and the defect classification was realized by Support vector machine(SVM),thus providing quality assurance for the secondary utilization of circuit boards.The influence of block size and judgment threshold on defect location results was analyzed,and the detection speed was significantly improved compared with the uniform block method while ensuring the detection accuracy.Compared with the Faster-RCNN method,the result showed that the proposed method had a good localization effect and the average classification accuracy was 81%.

Key words: machine vision, secondary utilization circuit board, surface defect detection, color histogram, quadtree splitting

摘要： 为了提高废旧电路板的回收再利用率,针对回收电路板常见表面缺陷,在均匀分块基础上,提出了四叉树分裂颜色直方图缺陷检测方法。该方法能快速定位电路板表面缺陷,并通过支持向量机(SVM)实现缺陷分类,进而为电路板的二次利用提供质量保障。重点分析了分块大小与判断阈值对缺陷定位结果的影响,在保证检测精度的同时,检测速度相比均匀分块方法得到明显提升。与Faster-RCNN网络方法进行对比,结果表明该方法定位效果好,分类准确率平均达81%。

关键词: 机器视觉, 二次利用电路板, 表面缺陷检测, 颜色直方图, 四叉树分裂