• DocumentCode
    598990
  • Title

    Local self-Similarity based texture classification

  • Author

    Hongbo Yang ; Xia Hou

  • Author_Institution
    Autom. Sch., Beijing Inf. Sci. & Technol. Univ., Beijing, China
  • fYear
    2012
  • fDate
    16-18 Oct. 2012
  • Firstpage
    795
  • Lastpage
    799
  • Abstract
    Aim of this paper is to develop a texture classification system for browsing and retrieval of image data. In this paper a novel local self-similarity texture descriptor is presented to describe the local texture pattern. And then, the classifier can be obtained by training local self-similarity texture descriptors captured from different textures. In this paper, the experiments are performed on the Brodatz texture database. And the results demonstrate that the proposed method is very efficient and can achieve high correct classification rate.
  • Keywords
    fractals; image classification; image retrieval; image texture; visual databases; Brodatz texture database; image data browsing; image data retrieval; local self-similarity texture descriptors training; local self-similarity-based texture classification; local texture pattern; Algorithm design and analysis; Classification algorithms; Databases; Feature extraction; Gabor filters; Image segmentation; Training; AdaBoost; local self-similarity; texture classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2012 5th International Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-0965-3
  • Type

    conf

  • DOI
    10.1109/CISP.2012.6469914
  • Filename
    6469914