Journal of South China University of Technology(Natural Science Edition) ›› 2012, Vol. 40 ›› Issue (1): 64-68,76.

• Mechanical Engineering • Previous Articles     Next Articles

Statistical Modeling-Based Image Matching Algorithm for Solder Joints of Electronic Components

Wu Hao  Zhang Xian-min  Kuang Yong-cong  Ouyang Gao-fei  Xie Hong-wei   

  1. School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2011-09-16 Revised:2011-10-11 Online:2012-01-25 Published:2011-12-01
  • Contact: 张宪民(1964-) ，男，教授，博士生导师，主要从事机构学、精密制造装备与现代控制技术等研究． E-mail: zhangxm@scut.edu.cn E-mail:wuhaomoses@ gmail.com
  • About author:吴浩(1986-) ，男，博士生，主要从事机器视觉检测研究．
  • Supported by:

    国家杰出青年基金资助项目( 50825504) ; NSFC-广东省自然科学联合基金资助项目( U0934004) ; 广东省高等学校珠江学者岗位计划( 2010) 资助项目; 广东省重大科技专项项目( 2009A080204005) ; 华南理工大学中央高校基本科研业务费专项资金资助项目( 2009ZM0073)

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Abstract:

In order to reduce the programming time and overcome the experience dependence on the existing automatic
optical inspection ( AOI) systems based on feature extraction,an image matching algorithm based on statistical
modeling is proposed. In this algorithm,first,qualified sample images of solder joints are separated from the unqualified ones in training. Next,a standard learning template image is formed through a gray-level statistical modeling of the qualified sample images. Then,after an alignment,the component image to be tested is matched with the trained template image. Finally,the difference in pixel point gray is calculated and is used to determine whether the testing component image is qualified or not. Experimental results show that the proposed algorithm,with a false alarm rate of less than 2% and a missing report rate of 0,helps to obtain satisfying accuracy of AOI and greatly reduces the programming time of users for inspection.

Key words: automatic optical inspection, solder joint, statistical modeling, image matching