• DocumentCode
    501263
  • Title

    Research of Image Retrieval Based on Uniting Features

  • Author

    Jinguang, Sun ; Zhipeng, Wang ; Da, Yin

  • Author_Institution
    Sch. of Economic Inf. Eng., Liaoning Tech. Univ., Huludao, China
  • Volume
    2
  • fYear
    2009
  • fDate
    15-17 May 2009
  • Firstpage
    603
  • Lastpage
    607
  • Abstract
    Research the current content-based image retrieval technology. In order to improve the limitations of single feature image retrieval and the computational complexity of integrated features image retrieval is so complexity, so it brings up a new method based on uniting features. The mainly theory is that combines Tamura texture feature with wavelet transform texture analysis of resist geometric distortions to extract 13-componet texture features; after the Daubechies3 wavelet transform, and extracts the color histogram and 7 shaped invariant moments at the low-frequency region; then implement a system of uniting features image retrieval. The Experiments show that it has better search results with no apparent increasing amount of calculation than the feature of a single or other integrated feature to retrieval.
  • Keywords
    content-based retrieval; image colour analysis; image retrieval; image texture; wavelet transforms; Daubechies3 wavelet transform; Tamura texture feature; color histogram; computational complexity; content-based image retrieval technology; geometric distortions; single feature image retrieval; uniting features image retrieval; wavelet transform texture analysis; Computational complexity; Content based retrieval; Feature extraction; Image analysis; Image color analysis; Image retrieval; Image texture analysis; Resists; Wavelet analysis; Wavelet transforms; color histogram; image retrieval; invariant moments; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications, 2009. IFITA '09. International Forum on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-0-7695-3600-2
  • Type

    conf

  • DOI
    10.1109/IFITA.2009.318
  • Filename
    5231422