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A Method of Supervised Discrimination of Textures Based on Serial Statistical Tests

  • Juliusz L. Kulikowski
  • Malgorzata Przytulska
  • Diana Wierzbicka
Part of the Advances in Soft Computing book series (AINSC, volume 30)

Abstract

It is presented a new type of learning textures recognition algorithms based on serial statistical tests. It is assumed that a texture can be formally represented by a multi-component random vector whose probabilistic characteristics are, in general, a priori unknown. Discrimination of textures is equivalent to a discrimination of random vectors of different but a priori unknown statistical properties. For this purpose non-parametric statistical tests based on serial statistics are used. Construction of serial statistics needs a linear ordering of multi-dimensional observation space. The method is illustrated by numerical examples.

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References

  1. 1.
    Bruno A., Collorec R., Bezy-Wendling J., et al. (1997). Texture Analysis in Medical Imaging. In: Roux C., Coatrieux J.-L. (eds) Contemporary Perspectives in Three-Dimensional Biomedical Imaging. IOS Press, Amsterdam: 133–164.Google Scholar
  2. 2.
    Kulikowski J.L., Wierzbicka D. (2004). Texture Analysis Based on Application of Non-Parametric Serial Statistical Tests. Biocybernetics and Biomedical Engineering vol. 24 No 2: 27–39.Google Scholar
  3. 3.
    Runyon R.P. (1977). Nonparametric Statistics. A Contemporary Approach. Addison-Wesley Publishing Company, Reading, Mass., USA.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Juliusz L. Kulikowski
    • 1
  • Malgorzata Przytulska
    • 1
  • Diana Wierzbicka
    • 1
  1. 1.Institute of Biocybernetics and Biomedical Engineering PASWarsawPoland

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