• DocumentCode
    2540165
  • Title

    Image retrieval based on an improved CS-LBP descriptor

  • Author

    Junding, Sun ; Shisong, Zhu ; Xiaosheng, Wu

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2010
  • fDate
    16-18 April 2010
  • Firstpage
    115
  • Lastpage
    117
  • Abstract
    The texture spectrum descriptors, center-symmetric local binary pattern (CS-LBP) and its extension D-LBP are effective for region description. However, they discard the low frequency information of a region. A novel improved operator, named ID-LBP, is proposed based on D-LBP in this paper. The new operator classifies the local pattern based on the relativity between the local gray mean and the center-symmetric pixels instead of the gray variation between the center-symmetric pixels and the center pixel as D-LBP. Comparisons are given among CS-LBP, D-LBP and ID-LBP on two commonly used image databases and the experimental results show the performance improvement of the new method.
  • Keywords
    image retrieval; image texture; object recognition; gray variation; image databases; image retrieval; improved CS-LBP descriptor; local binary pattern; texture spectrum descriptors; Computer science; Control engineering; Frequency; Histograms; Image databases; Image retrieval; Laboratories; Pattern analysis; Robustness; Sun; center-symmetric local binary pattern; direction local binary pattern; image retrieval; texture spectrum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5263-7
  • Electronic_ISBN
    978-1-4244-5265-1
  • Type

    conf

  • DOI
    10.1109/ICIME.2010.5477432
  • Filename
    5477432