• DocumentCode
    419747
  • Title

    A Gaussian mixture-based colour texture model

  • Author

    Haindl, M. ; Grim, J. ; Somol, P. ; Pudil, P. ; Kudo, M.

  • Author_Institution
    Inst. of Inf. Theor. & Autom., Acad. of Sci. of the Czech Republic, Prague, Czech Republic
  • Volume
    3
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    177
  • Abstract
    A new method of colour texture modelling based on Gaussian distribution mixtures is discussed. We estimate the local statistical properties of the monospectral version of the target texture in the form of a Gaussian mixture of product components. The synthesized texture is obtained by means of a step-wise prediction of the texture image. In order to achieve a realistic colour texture image and to avoid possible loss of high-frequency details we use optimally chosen pieces of the original colour source texture in the synthesis phase. In this sense the proposed texture modelling method can be viewed as a statistically controlled sampling. By using multispectral or mutually registered BTF texture pieces the method can be easily extended also for these textures.
  • Keywords
    Gaussian distribution; estimation theory; image colour analysis; image registration; image sampling; image texture; prediction theory; spectral analysis; Gaussian distribution mixtures; colour source texture; colour texture synthesis; estimation theory; image colour texture modelling; monospectral analysis; multispectral texture images; mutually registered bidirectional texture function; statistical property; statistically controlled sampling; step wise prediction; Artificial intelligence; Automation; Chromium; Control system synthesis; Gaussian distribution; Image sampling; Information theory; Mathematical model; Parameter estimation; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1334497
  • Filename
    1334497