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International Conference on Computer Vision, Imaging and Computer Graphics

VISIGRAPP 2009: Computer Vision, Imaging and Computer Graphics. Theory and Applications pp 357–369Cite as

Textured Image Segmentation Using Active Contours

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 68))

Abstract

In this paper, we propose a novel level set based active contour model to segment textured images. The proposed method is based on the assumption that local histograms of filtering responses between foreground and background regions are statistically separable. In order to be able to handle texture non-uniformities, which often occur in real world images, we use rotation invariant filtering features and local spectral histograms as image feature to drive the snake segmentation. Automatic histogram bin size selection is carried out so that its underlying distribution can be best represented. Experimental results on both synthetic and real data show promising results and significant improvements compared to direct modeling based on filtering responses.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Wales Swansea, Swansea, U.K.

    Xianghua Xie

Authors
  1. Xianghua Xie
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Editor information

Editors and Affiliations

  1. INSTICC, Avenida D. Manuel I, 2910, Setúbal, Portugal

    AlpeshKumar Ranchordas

  2. Departamento de Engenharia Informática, Instituto Superior Técnico, Av. Rovisco Pais, 1049-001, Lisboa, Portugal,

    João Madeiras Pereira

  3. Institute for Systems and Robotics, Department of Electrical and Computer Engineering Polo II, University of Coimbra, 3030-290, Coimbra, Portugal

    Hélder J. Araújo

  4. Departamento de Engenharia Mecânica e Gestão Industrial, Rua Dr. Roberto Frias, s/n, 4200-465, Porto, Portugal

    João Manuel R. S. Tavares

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© 2010 Springer-Verlag Berlin Heidelberg

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Xie, X. (2010). Textured Image Segmentation Using Active Contours. In: Ranchordas, A., Pereira, J.M., Araújo, H.J., Tavares, J.M.R.S. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Applications. VISIGRAPP 2009. Communications in Computer and Information Science, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11840-1_26

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  • DOI: https://doi.org/10.1007/978-3-642-11840-1_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11839-5

  • Online ISBN: 978-3-642-11840-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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