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Proceedings Paper

Modular approach to automatic printed circuit board inspection
Author(s): Madhav Moganti; Fikret Ercal; Venkatkrishna Yellepeddy
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Paper Abstract

Many vision problems are solved using knowledge-based approaches. The conventional knowledge-based systems use domain experts to generate the initial rules and their membership functions, and then by trial and error refine the rules a\nd membership functions to optimize the final system's performance. However, it would be difficult for human experts to examine all the input-output data in complex vision applications to find and tune the rules and functions within the system. Printed circuit board inspection is one such complex vision application. Our research introduces the application of fuzzy logic in printed circuit board inspection. The system presented here is highly modular and can handle most of the defects simultaneously with the same approach and is significantly faster compared to the existing approaches. This paper addresses three of the major components of the system: the first phase is the segmentation of the printed circuit board images into basic sub-patterns, the second is the learning phase, and finally the third component is the verification/inspection phase. The paper finally concludes with the experimental results.

Paper Details

Date Published: 21 February 1996
PDF: 12 pages
Proc. SPIE 2665, Machine Vision Applications in Industrial Inspection IV, (21 February 1996); doi: 10.1117/12.232241
Show Author Affiliations
Madhav Moganti, Univ. of Missouri/Rolla (United States)
Fikret Ercal, Univ. of Missouri/Rolla (United States)
Venkatkrishna Yellepeddy, Univ. of Missouri/Rolla (United States)

Published in SPIE Proceedings Vol. 2665:
Machine Vision Applications in Industrial Inspection IV
A. Ravishankar Rao; Ning Chang, Editor(s)

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