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INDEPENDENT COMPONENT ANALYSIS OF TEXTURES IN ANGIOGRAPHY IMAGES

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Computer Vision and Graphics

Part of the book series: Computational Imaging and Vision ((CIVI,volume 32))

Abstract

The technique of independent component analysis (ICA) is applied for texture feature detection. In ICA an optimal transformation (with respect to the statistical structure of the image samples set) is discovered via blind signal processing. Any texture is considered as a mixture of independent sources (basic functions of detected transformation). Experimental comparison is documented on the compactness and separability of base functions, the data-specific ICA-based and universal Gabor functions (the latter are set by default for all kinds of images).

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Author information

Authors and Affiliations

  1. Warsaw University of Technology, Inst. of Control and Computation Eng., ul. Nowowiejska 15/19, Warsaw, PL-00-665

    Ewa Snitkowska & Wlodzimierz Kasprzak

Authors
  1. Ewa Snitkowska
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  2. Wlodzimierz Kasprzak
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Editor information

Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    K. Wojciechowski

  2. Silesian University of Technology, Gliwice, Poland

    B. Smolka

  3. Silesian University of Technology, Gliwice, Poland

    H. Palus

  4. The University of Western Australia, Crawley, Australia

    R.S. Kozera

  5. Warsaw University of Technology, Warsaw, Poland

    W. Skarbek

  6. The University of Western Australia, Crawley, Australia

    L. Noakes

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© 2006 Springer

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Snitkowska, E., Kasprzak, W. (2006). INDEPENDENT COMPONENT ANALYSIS OF TEXTURES IN ANGIOGRAPHY IMAGES. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_53

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  • DOI: https://doi.org/10.1007/1-4020-4179-9_53

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4178-5

  • Online ISBN: 978-1-4020-4179-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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