• DocumentCode
    624658
  • Title

    A new texture feature extraction method for image retrieval

  • Author

    Li Zong ; Liu Ying ; Li Daxiang

  • Author_Institution
    Sch. of Commun. & Inf. Eng., Xi´an Univ. of Post & Telecommun., Xi´an, China
  • fYear
    2013
  • fDate
    9-11 June 2013
  • Firstpage
    482
  • Lastpage
    486
  • Abstract
    Contrast, as a type of Tamura texture feature, is a global variable which can well describe the statistical distribution of the brightness in the entire image, but can not reflect the local brightness information of the image. This paper proposes an improved method, which makes use of the statistical moments of intensity histogram to extract more information from the image. Tested on a tire tread pattern dataset, the proposed method provides better retrieval performance compared with existing methods. Hence, it is concluded that the proposed method is effective in texture feature description especially for type texture, due to the fact that more intensity information is exploited.
  • Keywords
    feature extraction; image retrieval; image texture; statistical analysis; Tamura texture feature extraction; global variable; image retrieval; intensity histogram; pattern dataset; statistical distribution; statistical moment; Brightness; Educational institutions; Feature extraction; Histograms; Image retrieval; Telecommunications; Tires; Contrast; Image Retrieval; Statistical moments; Tamura texture feature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-6248-1
  • Type

    conf

  • DOI
    10.1109/ICICIP.2013.6568122
  • Filename
    6568122