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Proceedings Paper

Automated and standardized high-resolution appearance imaging system for electronic components
Author(s): Yunhe Liu; Ke Wang; Jiyuan Liang; Junzhang Chen; Xiangzhi Bai; Fugen Zhou
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Paper Abstract

The rapid development of electronic industry not only increases the variety of electronic components, but also increases the difficulty of inspection work. To effectively improve the appearance inspection performance, an appearance imaging system based on machine vision is proposed in this paper. The system provides practical solutions for the following four problems. Firstly, to maintain the consistence of appearance images, a standardized imaging method is presented to unify imaging parameters. Secondly, when dealing with different reflection properties, we proposed a combined illumination method using light sources with different wave lengths to meet imaging needs. Thirdly, for large size objects, we put forward a method combined with size measurement and image mosaic to get high-resolution and panoramic images. Fourthly, this paper provides a method of 3D reconstruction based on monocular vision to reflect depth information and geometric characteristics of real scenes. In the meanwhile, we design associated software to achieve the auto-control. Experiment results conclude that it is effective to achieve standardized and high-resolution appearance imaging. The system builds up a good foundation for the subsequent inspection work. The research of this paper has a broad meaning and application prospect.

Paper Details

Date Published: 24 October 2017
PDF: 5 pages
Proc. SPIE 10462, AOPC 2017: Optical Sensing and Imaging Technology and Applications, 104623N (24 October 2017);
Show Author Affiliations
Yunhe Liu, BeiHang Univ. (China)
Ke Wang, China Academy of Launch Vehicle Technology (China)
Jiyuan Liang, China Academy of Launch Vehicle Technology (China)
Junzhang Chen, BeiHang Univ. (China)
Xiangzhi Bai, BeiHang Univ. (China)
Fugen Zhou, BeiHang Univ. (China)

Published in SPIE Proceedings Vol. 10462:
AOPC 2017: Optical Sensing and Imaging Technology and Applications
Yadong Jiang; Haimei Gong; Weibiao Chen; Jin Li, Editor(s)

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