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Proceedings Paper

Selecting image retrieval parameters with a genetic algorithm
Author(s): Barry I. Soroka; Steven P. Kerrick
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Paper Abstract

Image retrieval (IR) means taking a probe image and finding the most appropriate match in a (possibly very large) image database. Unlike keyword-indexing, our approach is to compute a feature vector (FV) for each image, and to compute the distance from the probe to each image in the database. As a starting point, we studied the system of Jacobs et al., developed at the University of Washington, which used the Haar wavelet transform to produce feature vectors from images. A genetic algorithm developed weighting parameters which yielded significantly improved image retrieval performance.

Paper Details

Date Published: 10 January 2003
PDF: 11 pages
Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); doi: 10.1117/12.476250
Show Author Affiliations
Barry I. Soroka, California State Polytechnic Univ./Pomona (United States)
Steven P. Kerrick, California State Polytechnic Univ./Pomona (United States)

Published in SPIE Proceedings Vol. 5021:
Storage and Retrieval for Media Databases 2003
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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