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

    Fingerprint

    Independent component analysis
    Image retrieval
    Image Retrieval
    Retrieval
    JPEG2000
    Query

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    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

    Sensibility-aware image retrieval using computationally learned bases : RIM, JPG, J2K, and their mixtures. / Kato, Takatoshi; Honma, Shun'Ichi; Matsuyama, Yasuo; Yoshino, Tetsuma; Hoshino, Yuuki.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5506 LNCS PART 1. ed. 2009. p. 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).

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

    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 edn, vol. 5506 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5506 LNCS, pp. 621-628, 15th International Conference on Neuro-Information Processing, ICONIP 2008, Auckland, 08/11/25. https://doi.org/10.1007/978-3-642-02490-0_76
    Kato T, Honma SI, Matsuyama Y, Yoshino T, Hoshino Y. 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. 2009. p. 621-628. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-02490-0_76
    Kato, Takatoshi ; Honma, Shun'Ichi ; Matsuyama, Yasuo ; Yoshino, Tetsuma ; Hoshino, Yuuki. / Sensibility-aware image retrieval using computationally learned bases : RIM, JPG, J2K, and their mixtures. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5506 LNCS PART 1. ed. 2009. pp. 621-628 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
    @inproceedings{327e266a34a94ff6a828ad1f0dffcb08,
    title = "Sensibility-aware image retrieval using computationally learned bases: RIM, JPG, J2K, and their mixtures",
    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.",
    author = "Takatoshi Kato and Shun'Ichi Honma and Yasuo Matsuyama and Tetsuma Yoshino and Yuuki Hoshino",
    year = "2009",
    doi = "10.1007/978-3-642-02490-0_76",
    language = "English",
    isbn = "3642024890",
    volume = "5506 LNCS",
    series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    number = "PART 1",
    pages = "621--628",
    booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    edition = "PART 1",

    }

    TY - GEN

    T1 - Sensibility-aware image retrieval using computationally learned bases

    T2 - RIM, JPG, J2K, and their mixtures

    AU - Kato, Takatoshi

    AU - Honma, Shun'Ichi

    AU - Matsuyama, Yasuo

    AU - Yoshino, Tetsuma

    AU - Hoshino, Yuuki

    PY - 2009

    Y1 - 2009

    N2 - 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.

    AB - 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.

    UR - http://www.scopus.com/inward/record.url?scp=70349100032&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=70349100032&partnerID=8YFLogxK

    U2 - 10.1007/978-3-642-02490-0_76

    DO - 10.1007/978-3-642-02490-0_76

    M3 - Conference contribution

    AN - SCOPUS:70349100032

    SN - 3642024890

    SN - 9783642024894

    VL - 5506 LNCS

    T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    SP - 621

    EP - 628

    BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    ER -