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Proceedings Paper

Learning algorithms for both real-time detection of solder shorts and for SPC measurement correction using cross-sectional x-ray images of PCBA solder joints
Author(s): Paul A. Roder
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Paper Abstract

Learning algorithms are introduced for use in the inspection of cross-sectional X-ray images of solder joints. These learning algorithms improve measurement accuracy by accounting for localized shading effects that can occur when inspecting double- sided printed circuit board assemblies. Two specific examples are discussed. The first is an algorithm for detection of solder short defects. The second algorithm utilizes learning to generate more accurate statistical process control measurements.

Paper Details

Date Published: 11 March 1994
PDF: 10 pages
Proc. SPIE 2183, Machine Vision Applications in Industrial Inspection II, (11 March 1994); doi: 10.1117/12.171225
Show Author Affiliations
Paul A. Roder, Four Pi Systems, a subsidiary of Hewlett-Packard Co. (United States)


Published in SPIE Proceedings Vol. 2183:
Machine Vision Applications in Industrial Inspection II
Benjamin M. Dawson; Stephen S. Wilson; Frederick Y. Wu, Editor(s)

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