Research on image segmentation technology for PCB inspection

ZENG Cheng; ZHAO Xi-jun; XU Xin; DONG Yi; HAN Yi-nan

doi:10.13873/j.1000-97872011.02.020

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Research on image segmentation technology for PCB inspection

更新时间：2025-09-11

- Research on image segmentation technology for PCB inspection
- Vol. 30, Issue 2, Pages: 26-28(2011)
- 作者机构：
  
  中国工程物理研究院电子工程研究所
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872011.02.020
  CLC： TN41;TP391.41
- Published：2011
- 稿件说明：
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[1]曾成,赵锡钧,徐欣,董义,韩依楠.PCB检测中图像分割技术研究[J].传感器与微系统,2011,30(02):26-28.

ZENG Cheng, ZHAO Xi-jun, XU Xin, et al. Research on image segmentation technology for PCB inspection[J]. 2011, 30(2): 26-28.
[1]曾成,赵锡钧,徐欣,董义,韩依楠.PCB检测中图像分割技术研究[J].传感器与微系统,2011,30(02):26-28. DOI： 10.13873/j.1000-97872011.02.020.

ZENG Cheng, ZHAO Xi-jun, XU Xin, et al. Research on image segmentation technology for PCB inspection[J]. 2011, 30(2): 26-28. DOI： 10.13873/j.1000-97872011.02.020.

摘要

光学检测是进行印刷电路板（PCB）装配质量检验的重要手段

应用图像分割技术可以提取PCB中的目标物以进行检测。针对PCB图像分割

提出一种基于改进量子遗传算法的图像分割方法。该方法将基于阈值的图像分割方法转化为阈值优化问题

通过改进量子遗传算法的计算实现最优图像分割阈值的求取。仿真结果验证了该方法的可行性。

Abstract

Optical inspection is an important means to examine PCB assembly quality.Image segmentation technology can be used to extract object on PCB and it could be examined.The problem of PCB image segmentation is studied.An approach based on improved quantum genetic algorithm is proposed to solve it.The approach transforms image segmentation based on threshold into optimization.Through it

optimumal image segmentation threshold could obtain.Simulations show that the algorithm is effective in image segmentation.

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references

一种基于遗传算法的最优阈值图像分割算法 [J]. 童小念,刘娜. 武汉理工大学学报(交通科学与工程版) . 2008(02)

多阈值图像分割的模糊粒子群优化算法 [J]. 许永峰,张书玲. 计算机工程与应用 . 2008(11)

改进量子遗传算法及其应用 [J]. 周传华,钱锋. 计算机应用 . 2008(02)

区域进化自适应高精度区域增长图像分割算法 [J]. 胡正平,张晔,谭营. 系统工程与电子技术 . 2007(06)

基于边缘检测的图像分割方法及其在机器鱼中的应用 [J]. 沈志忠,王硕,曹志强,谭民,王龙. 机器人 . 2006(04)

混合量子遗传算法及其性能分析 [J]. 王凌,吴昊,唐芳,郑大钟,金以慧. 控制与决策 . 2005(02)

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