• DocumentCode
    2227181
  • Title

    IISM: an image internal semantic model for image database based on relevance feedback

  • Author

    Duan, Lijuan ; Gao, Wen

  • Author_Institution
    The Coll. of Comput. Sci., Beijing Univ. of Technol., China
  • fYear
    2003
  • fDate
    13-17 Oct. 2003
  • Firstpage
    528
  • Lastpage
    531
  • Abstract
    A semantic model - IISM (image internal semantic model) is introduced. Unlike other semantic extracting methods, IISM extracts the semantic information not by image segmentation and image understanding, but by analyzing relevance feedback image retrieval results. For relevance feedback image retrieval system, the images relevant to query are pointed as positive example, otherwise the images irrelevant to query are pointed as negative examples. It is assumed that these positive examples are related in semantic content. IISM computes comprehensive pair-wise mutual information for all images through analyzing the results of relevance feedback image retrieval. An association with a high mutual information means that one image is semantically associated with another. Semantic retrieval and clustering is carried out based on these association relationships.
  • Keywords
    image retrieval; relevance feedback; IISM; image database; image internal semantic model; image retrieval system; query relevancy; relevance feedback; semantic extracting method; semantic information; Data mining; Feature extraction; Image analysis; Image databases; Image retrieval; Image segmentation; Information analysis; Information retrieval; Mutual information; Negative feedback;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, 2003. WI 2003. Proceedings. IEEE/WIC International Conference on
  • Print_ISBN
    0-7695-1932-6
  • Type

    conf

  • DOI
    10.1109/WI.2003.1241258
  • Filename
    1241258