Shape recognition using genetic algorithms

Ender Ozcan, Chilukuri K Mohan

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

7 Scopus citations

Abstract

Shape recognition is a challenging task when shapes overlap, forming noisy, occluded, partial shapes. This paper uses a genetic algorithm for matching input shapes with model shapes described in terms of features such as line segments and angles (extracted using traditional algorithms). The quality of matching is gauged using a measure derived from attributed shape grammars [12, 13]. Preliminary results, using shapes with about 30 features each, are extremely encouraging.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Evolutionary Computation
PublisherIEEE Computer Society
Pages411-416
Number of pages6
StatePublished - 1996
EventProceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 - Nagoya, Jpn
Duration: May 20 1996May 22 1996

Other

OtherProceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96
CityNagoya, Jpn
Period5/20/965/22/96

ASJC Scopus subject areas

  • Engineering(all)

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