Modular Approach to Automatic Printed Circuit Board Inspection


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 and 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.


Computer Science

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Article - Conference proceedings

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Final Version

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Publication Date

01 Jan 1996

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