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Hybrid Defect Detection Method Based on the Shape Measurement and Feature Extraction for Complex Patterns
Hilario Haruomi KOBAYASHI Yasuhiko HARA Hideaki DOI Kazuo TAKAI Akiyoshi SUMIYA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2000/07/25
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Machine Vision Applications)
printed circuit board, image processing, shape measurement, feature extraction, automatic inspection,
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The visual inspection of printed circuit boards (PCBs) at the final production stage is necessary for quality assurance and the requirements for an automated inspection system are very high. However, consistent inspection of patterns on these PCBs is very difficult due to pattern complexity. Most of the previously developed techniques are not sensitive enough to detect defects in complex patterns. To solve this problem, we propose a new optical system that discriminates pattern types existing on a PCB, such as copper, solder resist and silk-screen printing. We have also developed a hybrid defect detection technique to inspect discriminated patterns. This technique is based on shape measurement and features extraction methods. We used the proposed techniques in an actual automated inspection system, realizing real time transactions with a combination of hardware equipped with image processing LSIs and PC software. Evaluation with this inspection system ensures a 100% defect detection rate and a fairly low false alarm rate (0.06%). The present paper describes the inspection algorithm and briefly explains the automated inspection system.