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UNSUPERVISED SCALE-SPACE TEXTURE DETECTOR IN MULTI-CHANNEL IMAGES BASED ON THE STRUCTURAL TENSOR

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Computer Vision and Graphics

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

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Abstract

The paper addresses the problem of multi-spectral image segmentation based on texture detection in domain of scale-space. The main contribution of this paper is presentation of the robust image partitioning method based on the tensor operator for detection of local structures in neighborhoods of pixels. We also extend the concept of a structural tensor to multi- spectral images and discuss the two different concepts of a scale associated with this tensor. The presented method was tested with many different monochrome and color images. We provide the experimental results and details of implementation.

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Author information

Authors and Affiliations

  1. AGH – University of Science and Technology, Mickiewicza Avenue 30, Kraków, 30-059, Poland

    Boguslaw Cyganek

Authors
  1. Boguslaw Cyganek
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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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Cyganek, B. (2006). UNSUPERVISED SCALE-SPACE TEXTURE DETECTOR IN MULTI-CHANNEL IMAGES BASED ON THE STRUCTURAL TENSOR. 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_60

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  • DOI: https://doi.org/10.1007/1-4020-4179-9_60

  • 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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