Sensibility-aware image retrieval using computationally learned bases: RIM, JPG, J2K, and their mixtures

Takatoshi Kato, Shun'Ichi Honma, Yasuo Matsuyama, Tetsuma Yoshino, Yuuki Hoshino

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    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.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages621-628
    Number of pages8
    Volume5506 LNCS
    EditionPART 1
    DOIs
    Publication statusPublished - 2009
    Event15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland
    Duration: 2008 Nov 252008 Nov 28

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 1
    Volume5506 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other15th International Conference on Neuro-Information Processing, ICONIP 2008
    CityAuckland
    Period08/11/2508/11/28

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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  • Cite this

    Kato, T., Honma, SI., Matsuyama, Y., Yoshino, T., & Hoshino, Y. (2009). Sensibility-aware image retrieval using computationally learned bases: RIM, JPG, J2K, and their mixtures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 5506 LNCS, pp. 621-628). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5506 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-02490-0_76