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PalmPrints: A Novel Co-evolutionary Algorithm for Clustering Finger Images
Nawwaf Kharma, Ching Y. Suen, and Pei F. Guo
Departments of Electrical & Computer Engineering and Computer Science,
Concordia University,
1455 de Maisonneuve Blvd. West,
Montreal, QC, H3G 1M8, Canada
kharma@ece.concordia.ca
Abstract. The purpose of this study is to explore an alternative means of hand image classification, one that requires minimal human intervention. The main tool for accomplishing this is a Genetic Algorithm (GA). This study is more than just another GA application; it introduces (a) a novel cooperative co-evolutionary clustering algorithm with dynamic clustering and feature selection; (b) an extended fitness function, which is particularly suited to an integrated dynamic clustering space. Despite its complexity, the results of this study are clear: the GA evolved an average clustering of 4 clusters, with minimal overlap between them.
LNCS 2723, p. 322 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003