Vector classification of SMD images

J. Rene Villalobos, Miguel Arellano, Adolfo Medina, Fernando Aguirre

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

The automated visual inspection of surface-mounted devices (SMD) requires the correct classification of an image as either "component present" or "component absent." The inspection system must allow the classification to be fast and reliable while also assuring that the training of the classifier is simple and not time consuming. The traditional sequential approach to classifying images, while simple to implement, presents some disadvantages, including an increase in false alarm (type I) errors and the need for a time-consuming training phase. The method presented in this paper seeks to reduce classification errors by using a vector approach for the inspection of components. An experiment using real SMD inspection data is conducted to validate the performance of the proposed vector classifier. The results of the experiment support the hypothesis that the vector-based inspection approach renders fewer errors than the sequential inspection approach.

Original languageEnglish (US)
Pages (from-to)265-282
Number of pages18
JournalJournal of Manufacturing Systems
Volume22
Issue number4
DOIs
StatePublished - Jan 1 2003

Keywords

  • Automated Visual Inspection (AVI)
  • Electronics Assembly
  • Multivariate Discrimination
  • Vector Classifier

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Hardware and Architecture
  • Industrial and Manufacturing Engineering

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