Abstract
In this paper, we present a smart machine vision (SMV) system for printed circuit board (PCB) inspection. It has advantages over the traditional manual inspection by its higher efficiency and accuracy. This SMV system consists of two modules, LIF (Learning Inspection Features) and OLI (On-Line Inspection). The LIF module automatically learns inspection features from the CAD files of a PCB board. The OLI module runs on-line to inspect PCB boards using a high-resolution 2-D sensor and the knowledge provided by the LIF components. Key algorithms developed for SMV are presented in the paper. The SMV system can be deployed on a manufacturing line with a much more affordable price comparing to other commercial inspection systems.
Cite
CITATION STYLE
Chen, T. Q., Zhang, J., Zhou, Y., & Murphey, Y. L. (2001). A smart machine vision system for PCB inspection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2070, pp. 513–518). Springer Verlag. https://doi.org/10.1007/3-540-45517-5_57
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