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Shape Recognition by Voting on Fast Marching Iterations

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5807))

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Abstract

In this study, we present a Fast Marching (FM) - Shape Description integrated methodology that is capable both extracting object boundaries and recognizing shapes. A new speed formula is proposed, and the local front stopping algorithm in [1] is enhanced to freeze the active contour near real object boundaries. GBSD [2] is utilized as shape descriptor on evolving contour. Shape description process starts when a certain portion of the contour is stopped and continues with FM iterations. Shape description at each iteration is treated as a different source of shape information and they are fused to get better recognition results. This approach removes the limitation of traditional recognition systems that have only one chance for shape classification. Test results shown in this study prove that the voted decision result among these iterated contours outperforms the ordinary individual shape recognizers.

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Author information

Authors and Affiliations

  1. Computer Engineering Department, Istanbul Technical University, 34469, Ayazaga, Istanbul, Türkiye

    Abdulkerim Capar & Muhittin Gokmen

Authors
  1. Abdulkerim Capar
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  2. Muhittin Gokmen
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, CEP/GIP, 16 bis avenue Prieur de la côte d’or., 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Department of Telecommunication and Information Processing, Ghent University, St.-Pietersnieuwstraat 41, 9000, Gent, Belgium

    Wilfried Philips

  3. CSIRO ICT Centre, Epping, Po Box 76, 1710, Sydney, NSW, Australia

    Dan Popescu

  4. University of Antwerp, Universiteitsplein 1; Building N., 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2009 Springer-Verlag Berlin Heidelberg

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Capar, A., Gokmen, M. (2009). Shape Recognition by Voting on Fast Marching Iterations. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_35

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  • DOI: https://doi.org/10.1007/978-3-642-04697-1_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04696-4

  • Online ISBN: 978-3-642-04697-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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