Partial shape matching using genetic algorithms

Ender Ozcan, Chilukuri K. Mohan

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

Shape recognition is a challenging task when images contain overlapping, noisy, occluded, partial shapes. This paper addresses the task of matching input shapes with model shapes described in terms of features such as line segments and angles. The quality of matching is gauged using a measure derived from attributed shape grammars. We apply genetic algorithms to the partial shape-matching task. Preliminary results, using model shapes with 6 to 70 features each, are extremely encouraging.

Original languageEnglish (US)
Pages (from-to)987-992
Number of pages6
JournalPattern Recognition Letters
Volume18
Issue number10
DOIs
StatePublished - Oct 1997

Keywords

  • Attributed strings
  • Genetic algorithms
  • Partial shape matching
  • Pattern recognition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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