Image annotation fusing content-based and tag-based technique using support vector machine and vector space model

Shan Bin Chan, Hayato Yamana, Duy Dinh Le, Shinichi Satoh

    研究成果: Conference contribution

    2 被引用数 (Scopus)

    抄録

    In this paper, we propose a new image annotation method by combining content-based image annotation and tag-based image annotation techniques. Content-based image annotation technique is adopted to extract 'loosely defined concepts' by analyzing pre-given images' features such as color moment (CM), edge orientation histogram (EOH), and local binary pattern (LBP), followed by constructing a set of SVMs for 100 loosely defined concepts. A base-vector for each concept, similar to tag-based image annotation technique, is then constructed by using SVMs' predicted probabilistic results for sample-images whose main concepts are known. Finally cosine similarity between a query-image vector and the base vector is calculated for each concept. Experimental results show that our proposed method outperforms content-based image annotation technique by about 23% in accuracy.

    本文言語English
    ホスト出版物のタイトルProceedings - 10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ272-276
    ページ数5
    ISBN(電子版)9781479979783
    DOI
    出版ステータスPublished - 2014
    イベント10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014 - Marrakech, Morocco
    継続期間: 2014 11 232014 11 27

    Other

    Other10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014
    国/地域Morocco
    CityMarrakech
    Period14/11/2314/11/27

    ASJC Scopus subject areas

    • コンピュータ グラフィックスおよびコンピュータ支援設計
    • 信号処理
    • コンピュータ ネットワークおよび通信

    フィンガープリント

    「Image annotation fusing content-based and tag-based technique using support vector machine and vector space model」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

    引用スタイル