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Similarity-based image retrieval system using partitioned iterated function system codes

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Abstract

We propose a new image retrieval system using partitioned iterated function system (PIFS) codes. In PIFS encoding, a compression code contains mapping information between similar regions in the same image. This mapping information can be treated as vectors, and representative vectors can be generated using them. Representative vectors describe the features of the image. Hence, the similarity between images is directly calculable from representative vectors. This similarity is applicable to image retrieval. In this article, we explain this scheme and demonstrate its efficiency experimentally.

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Authors and Affiliations

  1. Graduate School of Information Systems, University of Electro-Communications, 1-5-1 Chofugaoka, 182-8585, Chofu, Japan

    Takanori Yokoyama, Ken Sugawara & T. Watanabe

Authors
  1. Takanori Yokoyama
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  2. Ken Sugawara
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  3. T. Watanabe
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Corresponding author

Correspondence to Takanori Yokoyama.

Additional information

This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24#x2013;26, 2003

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Yokoyama, T., Sugawara, K. & Watanabe, T. Similarity-based image retrieval system using partitioned iterated function system codes. Artif Life Robotics 8, 118–122 (2004). https://doi.org/10.1007/s10015-004-0297-5

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  • DOI: https://doi.org/10.1007/s10015-004-0297-5

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