DocumentCode :
782364
Title :
Automatic solder joint inspection
Author :
Bartlett, S.L. ; Besl, P.J. ; Cole, Charles L. ; Jain, R. ; Mukherjee, Debashish ; Skifstad, Kurt D.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Volume :
10
Issue :
1
fYear :
1988
fDate :
1/1/1988 12:00:00 AM
Firstpage :
31
Lastpage :
43
Abstract :
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
Keywords :
computer vision; computerised pattern recognition; electronic engineering computing; expert systems; inspection; printed circuit testing; PCBs; automatic joint inspection; classification evidence; computer vision; decorrelation; expert systems; feature data; feature weights; objective dimensionality-reduction method; pin-in-hole solder joints; statistical pattern recognition; voting scheme; Assembly; Costs; Decorrelation; Expert systems; Humans; Inspection; Pattern recognition; Printed circuits; Production; Soldering;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.3865
Filename :
3865
Link To Document :
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