Feature extraction and classification by genetic programming

Authors:
Olly Oechsle;Adrian F. Clark
Affiliations:
VASE Laboratory, Department of Computing and Electronic Systems, University of Essex, Colchester, UK;VASE Laboratory, Department of Computing and Electronic Systems, University of Essex, Colchester, UK
Venue:
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Year:
2008

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Abstract

This paper explores the use of genetic programming for constructing vision systems. A two-stage approach is used, with separate evolution of the feature extraction and classification stages. The strategy taken for the classifier is to evolve a set of partial solutions, each of which works for a single class. It is found that this approach is significantly faster than conventional genetic programming, and frequently results in a better classifier. The effectiveness of the approach is explored on three classification problems.