• 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