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Automatic solder joint inspection

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6 Author(s)
S. L. Bartlett ; Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA ; P. J. Besl ; C. L. Cole ; R. Jain
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The task of automating the visual inspection of pin-in-hole solder joints is addressed. Two approaches are explored: statistical pattern recognition and expert systems. An objective dimensionality-reduction method is used to enhance the performance of traditional statistical pattern recognition approaches by decorrelating feature data, generating feature weights, and reducing run-time computations. The expert system uses features in a manner more analogous to the visual clues that a human inspector would rely on for classification. Rules using these cues are developed, and a voting scheme is implemented to accumulate classification evidence incrementally. Both methods compared favorably with human inspector performance

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:10 ,  Issue: 1 )