| 基于图像特征统计分析的PCB焊点检测方法 |
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| 引用本文： | 谢宏威,张宪民,邝泳聪. 基于图像特征统计分析的PCB焊点检测方法[J]. 仪器仪表学报, 2011, 32(2) |
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| 作者姓名： | 谢宏威 张宪民 邝泳聪 |
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| 作者单位： | 华南理工大学机械与汽车工程学院,广州,510640 |
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| 摘 要： | 提出了一种基于图像特征统计分析的炉后焊点检测方法,以提高在线自动光学检测系统的检测性能和可操作性.提出双阈值的AdaBoost算法用于设计分类器,在训练的同时进行最优特征选择和分类器的增强,实现了焊点图像特征的自动提取和检测参数的自动设定.采用分类和回归树方法将焊点缺陷决策方法优化为一棵二叉决策树,提高了检测速度.实验结果表明,该方法训练速度较快,可以满足实际生产需要.与目前已经实用化的图像对比算法和图像分析算法相比,在保持现有检测速度基本不变的情况下,该方法的检测精度更高.
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| 关 键 词： | 自动光学检测 特征选择 缺陷决策 统计学习 |
Solder joint inspection method based on image feature statistical analysis |
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| Xie Hongwei,Zhang Xianmin,Kuang Yongcong. Solder joint inspection method based on image feature statistical analysis[J]. Chinese Journal of Scientific Instrument, 2011, 32(2) |
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| Authors: | Xie Hongwei Zhang Xianmin Kuang Yongcong |
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| Affiliation: | Xie Hongwei,Zhang Xianmin,Kuang Yongcong(School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,China) |
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| Abstract: | In order to improve the performance and maneuverability of online automatic optical inspection system,a novel method for post-reflow solder joint inspection based on image feature statistical analysis is proposed in this paper.Dual-threshold AdaBoost algorithm is used to design the classifier.Optimal features are selected and classifier is enhanced during the training process.Features of the solder joints are selected and detection parameters are set automatically.The solder joint defect decision method is ... |
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| Keywords: | automatic optical inspection feature selection defect decision statistical learning |
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