language: en

PARTIAL SHAPE MATCHING USING GENETIC ALGORITHMS

Ender Ozcan and Chilukuri K. Mohan
eozcan/mohan@top.cis.syr.edu
2-120 Center for Science and Technology,
Department of Electrical Engineering and Computer Science, Syracuse University,
Syracuse, NY 13244-4100, U.S.A.

[315-443-2322/(fax) 1122]

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.

Key words : Partial Shape Matching, Genetic Algorithms, Attributed Strings, Pattern Recognition.