Development of a methodology for the rapid self training automated visual inspection systems

L. Williams, F. Aguirre, Jesus Villalobos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The electronics assembly industry has faced the problem of rapid introduction and retirement of electronic products. Therefore, a system is required that automatically and significantly shortens the time to develop inspection algorithms for new components. The general goal of this research is to develop a self-training classifier for the inspection of SMD components. During the training of the classifier, feature selection is necessary to reduce the computational cost. In particular, this paper explores the use of linear regression as a way to measure the behavior of the features in order to expedite the feature selection process.

Original languageEnglish (US)
Title of host publicationIIE Annual Conference and Exhibition 2004
Pages1421-1426
Number of pages6
StatePublished - 2004
EventIIE Annual Conference and Exhibition 2004 - Houston, TX, United States
Duration: May 15 2004May 19 2004

Other

OtherIIE Annual Conference and Exhibition 2004
CountryUnited States
CityHouston, TX
Period5/15/045/19/04

Keywords

  • Automated visual inspection (AVI)
  • Feature selection
  • Linear regression
  • Statistical process control (SPC)
  • Vector classifier

ASJC Scopus subject areas

  • Engineering(all)

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