• DocumentCode
    3062022
  • Title

    An Effective Image Retrieval Method Based on Color and Texture Combined Features

  • Author

    Liu, Pengyu ; Jia, Kebin ; Wang, Zhuozheng

  • Author_Institution
    Beijing Univ. of Technol., Beijing
  • Volume
    1
  • fYear
    2007
  • fDate
    26-28 Nov. 2007
  • Firstpage
    169
  • Lastpage
    172
  • Abstract
    Image has various inherent features which reflect its content such as color, texture, shape, spatial relationship features etc. How to organize and utilize these features effectively and improve the retrieval performance is a valuable research topic. One of the key issues in image retrieval based on combined features is how to assign weight to different features. An image retrieval method combined color and texture features is proposed in this paper. According to image texture characteristic, a kind of image feature statistic is defined. By using feature weight assignment operators designed here, the method can assign weight to color and texture features according to image content adaptively and realize image retrieval based on combined image features. The experiment results show that the method mentioned above is more efficiently than those traditional image retrieval methods based on single visual feature or simple linear combined low- level visual features of fixed weight.
  • Keywords
    image colour analysis; image retrieval; image texture; color features; feature weight assignment operators; image feature statistic; image retrieval; image texture; texture features; Color; Content based retrieval; Control engineering; Educational institutions; Histograms; Image retrieval; Image texture; Information retrieval; Shape; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-0-7695-2994-1
  • Type

    conf

  • DOI
    10.1109/IIH-MSP.2007.79
  • Filename
    4457518