• DocumentCode
    3228765
  • Title

    A metric algorithm based on three elements of texture visual feature

  • Author

    Ying, Zhao Hal ; Mei, Xu Guang ; Yu, Sun Feng

  • Author_Institution
    Coll. of Math.-Phys. & Inf. Sci., Xinjiang Normal Univ., Urumqi, China
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    1221
  • Lastpage
    1224
  • Abstract
    In order to construct a reference model to recognize image texture, a combining method based on three elements of texture visual features is proposed. Firstly, a fractal model is used to calculate the fractal dimension which is a measure of image textural coarseness. Secondly, a global texture direction is proposed. Gabor filter and local marginal probability histogram is used to calculate a quantitative value of texture direction. Thirdly, the texture contrast base on Tamura model is applied to describe image texture feature. Finally, the combined method based on the coarseness, the direction and the contrast is applied to extract texture visual features in Brodatz texture database. The experimental result is consistent with human visual perception. The algorithm can be better reference model to satisfy machine identification image texture.
  • Keywords
    Gabor filters; feature extraction; fractals; image texture; probability; Gabor filter; Tamura model; fractal dimension; global texture direction; human visual perception; image textural coarseness; image texture feature; local marginal probability histogram; metric algorithm; texture contrast; texture visual feature extraction; Image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645151
  • Filename
    5645151