锥束CT图像中的印刷电路板导线自动检测方法

乔凯; 陈健; 李中国; 曾磊; 闫镔

doi:10.3788/OPE.20162402.0413

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锥束CT图像中的印刷电路板导线自动检测方法

信息科学 | 更新时间：2020-08-13

- 锥束CT图像中的印刷电路板导线自动检测方法
- Automatic printed circuit board wire detecting method of cone beam CT image
- 光学精密工程 2016年24卷第2期页码：413-421
- 作者机构：
  
  解放军信息工程大学信息系统工程学院,河南郑州,450001
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.61372172)()
- DOI：10.3788/OPE.20162402.0413
  中图分类号： TP391
- 收稿日期：2015-10-02，
  
  修回日期：2015-11-30，
  
  纸质出版日期：2016-02-25
- 稿件说明：
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乔凯, 陈健, 李中国等. 锥束CT图像中的印刷电路板导线自动检测方法[J]. 光学精密工程, 2016,24(2): 413-421

QIAO Kai, CHEN Jian, LI Zhong-guo etc. Automatic printed circuit board wire detecting method of cone beam CT image[J]. Editorial Office of Optics and Precision Engineering, 2016,24(2): 413-421
乔凯, 陈健, 李中国等. 锥束CT图像中的印刷电路板导线自动检测方法[J]. 光学精密工程, 2016,24(2): 413-421 DOI： 10.3788/OPE.20162402.0413.

QIAO Kai, CHEN Jian, LI Zhong-guo etc. Automatic printed circuit board wire detecting method of cone beam CT image[J]. Editorial Office of Optics and Precision Engineering, 2016,24(2): 413-421 DOI： 10.3788/OPE.20162402.0413.

摘要

针对印刷电路板(PCB)的CT图像存在灰度不均匀、导线形状多变等特点导致的导线难以有效检测的问题

提出了一种基于超像素分割的PCB导线自动检测方法。该方法使用基于引导滤波的类顶帽变换对图像预处理

提高不同类别区域的类间差异

改善后续的超像素分割结果;然后选择graph-based超像素分割算法对导线定位;最后

采用导线几何形状、灰度分布等特征判断识别导线区域

实现导线检测。对存在灰度不均匀、多条导线、多尺度的PCB CT图像进行了实际实验。结果显示:该算法取得了较好的导线检测结果

在实验测试图像上检测率达到了90%以上

基本满足导线自动检测对精度和抗干扰能力的要求

具有较高的应用价值。

Abstract

The CT image of Printed Circuit Board(PCB) exists problems in grey inhomogeneity

changeable and irregular wire shapes

so it is difficult to be detected efficiently. This paper proposes an automatic PCB wire detecting method based on superpixel segmentation. The comparably top-hat transform based on a guided filtering was used to preprocess images and to improve the interclass difference of different regions and the subsequent superpixel segmentation results. Then

the graph-based segmentation algorithm was selected to achieve the wire positioning. Finally

the wire region was identified by using the geometry and grayscale distribution features of the wire to implement the wire detection. The experiments for the PCB CT images with inhomogeneity grey

multi-wire and multi-scales were performed. The results show that the algorithm is able to overcome the intensity inhomogeneity of PCB CT image and achieves a better result with a detection rate more than 90%. It concludes that the algorithm satisfies higher precision and strong anti-jamming requirements for automatic detection of the wires of PCBs and has high application values.

关键词

Keywords

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