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Sensibility-Aware Image Retrieval Using Computationally Learned Bases: RIM, JPG, J2K, and Their Mixtures

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Advances in Neuro-Information Processing (ICONIP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5506))

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Abstract

Sensibility-aware image retrieval methods are presented and their performances are compared. Three systems are discussed in this paper: PCA/ICA-based method called RIM (Retrieval-aware IMage format), JPEG, and JPEG2000. In each case, a query is an image per se. Similar images are retrieved to this query. The RIM method is judged to be the best settlement in view of the retrieval performance and the response speed according a carefully designed set of opinion tests. An integrated retrieval system for image collections from the network and databases which contain RIM, JPEG and JPEG2000 is realized and evaluated lastly. Source codes of the RIM method is opened.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Waseda University, Tokyo, 169-8555, Japan

    Takatoshi Kato, Shun’ichi Honma, Yasuo Matsuyama, Tetsuma Yoshino & Yuuki Hoshino

  2. SONY, Tokyo, 108-0075, Japan

    Shun’ichi Honma

Authors
  1. Takatoshi Kato
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  2. Shun’ichi Honma
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  3. Yasuo Matsuyama
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  4. Tetsuma Yoshino
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  5. Yuuki Hoshino
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Editor information

Editors and Affiliations

  1. Kyushu Institute of Technology, Network Design and Research Center, 680-4 Fukuoka, 820-8502, Kawazu, Iizuka, Japan

    Mario Köppen

  2. Knowledge Engineering and Discovery Research Institute (KEDRI), School of Computing and Mathematical Sciences, Auckland University of Technology, 350 Queen Street, 10110, Auckland, New Zealand

    Nikola Kasabov

  3. Department of Electrical and Computer Engineering, Robotics Laboratory, Auckland University of Technology, 38 Princes Street, 1142, Auckland, New Zealand

    George Coghill

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© 2009 Springer-Verlag Berlin Heidelberg

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Kato, T., Honma, S., Matsuyama, Y., Yoshino, T., Hoshino, Y. (2009). Sensibility-Aware Image Retrieval Using Computationally Learned Bases: RIM, JPG, J2K, and Their Mixtures . In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_76

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  • DOI: https://doi.org/10.1007/978-3-642-02490-0_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02489-4

  • Online ISBN: 978-3-642-02490-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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