• DocumentCode
    2736333
  • Title

    A method of measuring the semantic gap in image retrieval: Using the information theory

  • Author

    Liu, Chengjun ; Song, Guangwei

  • Author_Institution
    Manage. Dept., Shenzhen Univ., Shenzhen, China
  • fYear
    2011
  • fDate
    21-23 Oct. 2011
  • Firstpage
    287
  • Lastpage
    291
  • Abstract
    The semantic gap exists in content-based image retrieval. Many researchers have proposed a variety of methods to bridge or narrow this gap. The methods include into two types: bottom-up and top-down approaches. These approaches have made great progress, but few studies have been done in how to measure it. In this paper, we redefine the semantic gap in a user-centered way and present a method for measuring the semantic gap, using the information theory.
  • Keywords
    content-based retrieval; image retrieval; information theory; bottom-up approach; content-based image retrieval; information theory; semantic gap measurement method; top-down approach; Computers; Feature extraction; Image color analysis; Image retrieval; Ontologies; Semantics; Sun; content-based image retrieval; definition; information entropy; measuring; semantic gap;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Signal Processing (IASP), 2011 International Conference on
  • Conference_Location
    Hubei
  • Print_ISBN
    978-1-61284-879-2
  • Type

    conf

  • DOI
    10.1109/IASP.2011.6109048
  • Filename
    6109048