中国机械工程2012，Vol.23Issue(22)：2661-2666,6.DOI:10.3969/j.issn.1004-132X.2012.22.004
基于机器视觉的PCB裸板缺陷自动检测方法
Automatic Defect Inspection of PCB Bare Board Based on Machine Vision
摘要
Abstract
An algorithm was proposed for defect inspection of PCB bare board. It was based on comparison between the standard PCB image and the target image and analysed the boundaries of the different regions in the target image. Multiple images were acquired for the qualified PCB at the same position,and an average was applied as the standard image. Then the target image was compared with it. On the PCB image there symmetrically distributed some vertical mark lines. First,these mark lines were detected rapidly by restricted areas Hough transform and the intersection of the lines were chosen as the feature point. Then the affine registration between the target image and the standard image could be completed. After subtraction,false defects were removed by threshold segmentation and morphological processing in the difference images. The locations of defect areas were obtained. The difference image was in the process of dilation,then the coordinate values of each defect area closed contour points could be obtained by boundary detection. The aligned target image was treated with threshold segmentation. In the processed image,the pixel values of the points whose coordinate values had been get above were obtained. According to the analysis of the pixel values and the judgment of whether the defect was lack of material or not, the type of detects could be quickly determined. The experimental results on 400 PCB images indicate that the correction rate of detection is of 98. 3%. The algorithm can accurately detect conventional defect steadily.关键词
机器视觉/PCB缺陷检测/Hough变换/边界分段Key words
machine vision/ printed circuit board(PCB) defect inspection/hough transform/ boundary segmentation分类
信息技术与安全科学引用本文复制引用
杨庆华,陈亮,荀一,陈文彪..基于机器视觉的PCB裸板缺陷自动检测方法[J].中国机械工程,2012,23(22):2661-2666,6.基金项目
国家高技术研究发展计划(863计划)资助项目(2009AA04Z209) （863计划）
浙江省自然科学基金杰出青年团队项目(R1090674) （R1090674）
浙江省特种装备制造与先进加工技术重点实验室开放基金资助项目(2011EM002) （2011EM002）
