• DocumentCode
    2112663
  • Title

    Texture classification using statistical geometrical features

  • Author

    Chen, Yan ; Nixon, Mark S. ; Thomas, David W.

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Southampton Univ., UK
  • Volume
    3
  • fYear
    1994
  • fDate
    13-16 Nov 1994
  • Firstpage
    446
  • Abstract
    This paper presents a new texture feature set based on the statistics of geometrical attributes of connected regions in a stack of binary images obtained from a texture image. Systematic evaluation using all the Brodatz textures shows that the new set outperforms the well-known statistical gray level dependence matrix, the recently proposed statistical feature matrix, and Liu´s features
  • Keywords
    feature extraction; geometry; image classification; image texture; statistics; Brodatz textures; binary images; connected regions; geometrical attributes; statistical geometrical features; texture classification; texture image; Computer science; Formal languages; Fourier transforms; Image texture analysis; Medical diagnosis; Pixel; Quality control; Remote sensing; Statistics; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
  • Conference_Location
    Austin, TX
  • Print_ISBN
    0-8186-6952-7
  • Type

    conf

  • DOI
    10.1109/ICIP.1994.413767
  • Filename
    413767