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Optimum Design of Dynamic Parameters of Active Contours for Improving Their Convergence in Image Segmentation

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3708))

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Abstract

Active contours are useful tools for segmenting images. The classical formulation is given in the spatial domain and is based on a second order system. The formulation based on a frequency-domain analysis offers a new perspective for studying the convergence of the snake. This paper addresses an analysis and optimization for a snake-based segmentation algorithm. The study allows us to choose optimum values of the system dynamic parameters in the design of the active contour for improving its speed of convergence in a segmentation problem.

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References

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Author information

Authors and Affiliations

  1. Department of Information Technologies and Communications, Technical University of Cartagena, 30202, Cartagena, Spain

    Rafael Verdú & Juan Morales

  2. Department of Technical Sciences, Catholic University of Murcia, 30107, Murcia, Spain

    Rafael Berenguer

  3. Commission for Scientific Visualization, Austrian Academy of Sciences, Donau-City Strasse 1, 1220, Vienna, Austria

    Luis Weruaga

Authors
  1. Rafael Verdú
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  2. Juan Morales
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  3. Rafael Berenguer
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  4. Luis Weruaga
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Ghent University, 9000, Gent, Belgium

    Wilfried Philips

  3. Wireless Technologies Lab, CSIRO ICT Centre, NSW 2122, Marsfield, Australia

    Dan Popescu

  4. University of Antwerp, 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2005 Springer-Verlag Berlin Heidelberg

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Verdú, R., Morales, J., Berenguer, R., Weruaga, L. (2005). Optimum Design of Dynamic Parameters of Active Contours for Improving Their Convergence in Image Segmentation. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_61

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  • DOI: https://doi.org/10.1007/11558484_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29032-2

  • Online ISBN: 978-3-540-32046-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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