Similarity-based retrieval method for fractal coded images in the compressed data domain

Authors:
Takanori Yokoyama;Toshinori Watanabe;Hisashi Koga
Affiliations:
Graduate School of Information Systems, University of Electro-Communications, Tokyo, Japan;Graduate School of Information Systems, University of Electro-Communications, Tokyo, Japan;Graduate School of Information Systems, University of Electro-Communications, Tokyo, Japan
Venue:
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Year:
2005

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Abstract

We propose a novel retrieval method for fractal coded images in the compressed data domain. A fractal code is a contractive affine mapping that represents a similarity relation between two regions in an image. A fractal coded image consists of a set of these contractive mappings. Each mapping can be approximately represented by a vector spanning two regions. Therefore, a fractal coded image can be approximated as a set of vectors. By introducing a new similarity measure that reflects the difference of distribution and cardinality between two vector sets, a novel retrieval method for fractal coded images is realized. We also propose a new efficient retrieval method using upper bounds of the similarity measure. The effectiveness of the proposed method is also illustrated by various experiments.