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Fast content-based image retrieval using quasi-Gabor filter and reduction of image feature dimension

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3 Author(s)
M. Park ; Sch. of Comput. Sci. & Eng., Univ. of NSW, Australia ; J. S. Jin ; L. S. Wilson

This paper introduces a new approach to content based image retrieval by texture. There are three problems to solve: high computational time, handling high dimension data, and comparing images consistent with human perception. To decrease the computational, time, we present a new strategy to extract an image feature with high retrieval accuracy. We also propose how to reduce the image feature dimension using the reward-punishment algorithm, so any robust indexing methods can be used. By weighting the extracted image features, a system may perceive the image consistently with human perception

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Image Analysis and Interpretation, 2002. Proceedings. Fifth IEEE Southwest Symposium on

Date of Conference: