• DocumentCode
    2852754
  • Title

    Improving image retrieval performance by using both color and texture features

  • Author

    Zhang, Dengsheng

  • Author_Institution
    Gippsland Sch. of Comput. & Inf., Tech. Monash Univ., Churchill, Vic., Australia
  • fYear
    2004
  • fDate
    18-20 Dec. 2004
  • Firstpage
    172
  • Lastpage
    175
  • Abstract
    Most content-based image retrievals (CBIR) use color as image features. However, image retrieval using color features often gives disappointing results because in many cases, images with similar colors do not have similar content. Color methods incorporating spatial information have been proposed to solve this problem, however, these methods often result in very high dimensions of features which drastically slow down the retrieval speed. In this paper, a method combining both color and texture features of image is proposed to improve the retrieval performance. Given a query, images in the database are firstly ranked using color features. Then, the top ranked images are re-ranked according to their texture features. Results show the second process improves retrieval performance significantly.
  • Keywords
    content-based retrieval; image colour analysis; image retrieval; image texture; content-based image retrieval; image texture; Australia; Content based retrieval; Feature extraction; Histograms; Image databases; Image retrieval; Information retrieval; Robustness; Shape; Spatial databases; CBIR; color; image retrieval; texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG'04), Third International Conference on
  • Conference_Location
    Hong Kong, China
  • Print_ISBN
    0-7695-2244-0
  • Type

    conf

  • DOI
    10.1109/ICIG.2004.86
  • Filename
    1410413