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Similarity-Based Retrieval Method for Fractal Coded Images in the Compressed Data Domain

  • Takanori Yokoyama
  • Toshinori Watanabe
  • Hisashi Koga
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3568)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Takanori Yokoyama
    • 1
  • Toshinori Watanabe
    • 1
  • Hisashi Koga
    • 1
  1. 1.Graduate School of Information SystemsUniversity of Electro-CommunicationsTokyoJapan

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