Palmprints: a novel co-evolutionary algorithm for clustering finger images

Authors:
Nawwaf Kharma;Ching Y. Suen;Pei F. Guo
Affiliations:
Departments of Electrical & Computer Engineering and Computer Science, Concordia University, Montreal, QC, Canada;Departments of Electrical & Computer Engineering and Computer Science, Concordia University, Montreal, QC, Canada;Departments of Electrical & Computer Engineering and Computer Science, Concordia University, Montreal, QC, Canada
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Year:
2003

Citing 6
Cited 1

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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.