Visual defectives inspection and classification using a multi-layer perceptron

Tai Oun Kim, Soundar R.T. Kumara, Rangachar Kasturi

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

This paper proposes an efficient feature representation scheme for a visual inspection problem which uses curvature and an iterative circular fitting algorithm. Homogeneous ranges as well as critical points on the boundary such as vertices, inflection points, linear, and circular features can be detected. Thus, a shape boundary can be represented by the combination of linear and circular features. For the classification purposes, a multi-layer perception which takes separated local features as input parameters, has been adopted. The test results showed that they are robust within some error range.

Original languageEnglish (US)
Pages743-748
Number of pages6
StatePublished - Dec 1 1993
EventProceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93 - St.Louis, MO, USA
Duration: Nov 14 1993Nov 17 1993

Other

OtherProceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93
CitySt.Louis, MO, USA
Period11/14/9311/17/93

All Science Journal Classification (ASJC) codes

  • Software

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    Kim, T. O., Kumara, S. R. T., & Kasturi, R. (1993). Visual defectives inspection and classification using a multi-layer perceptron. 743-748. Paper presented at Proceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93, St.Louis, MO, USA, .