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Convolutional Virtual Electric Field External Force for Active Contours

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Computer Vision – ACCV 2009 (ACCV 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5996))

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Abstract

A novel external force called CONvolutional Virtual Electric Field (CONVEF) for active contours is proposed by taking the Virtual Electric Field (VEF) just as a convolution operation and by using modified distance metrics in the convolution kernel. The proposed CONVEF method possesses some desirable properties of VEF such as large capture range and being implemented in real-time by using fast Fourier transform. Meanwhile, the CONVEF snake provides much better segmentation than VEF snake in terms of noise suppression, C-shape concavity convergence, weak edge preserving, and neighbored objects separation. These advantages has been demonstrated and verified on synthetic and real images.

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Author information

Authors and Affiliations

  1. Tianjin Key Lab of Intelligent Computing and Novel Software Technology, School of Computer Science, Tianjin University of Technology, Tianjin, 300191, P.R. China

    Yuanquan Wang

  2. Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, 100081, P.R.China

    Yuanquan Wang & Yunde Jia

Authors
  1. Yuanquan Wang
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  2. Yunde Jia
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Editor information

Editors and Affiliations

  1. Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Hongbin Zha

  2. Department of Advanced Information Technology, Kyushu University, 819-0395, Fukuoka, Japan

    Rin-ichiro Taniguchi

  3. Birkbeck College, Department of Computer Science, University of London, WC1E 7HX, London, UK

    Stephen Maybank

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© 2010 Springer-Verlag Berlin Heidelberg

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Wang, Y., Jia, Y. (2010). Convolutional Virtual Electric Field External Force for Active Contours. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12297-2_2

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  • DOI: https://doi.org/10.1007/978-3-642-12297-2_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12296-5

  • Online ISBN: 978-3-642-12297-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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