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Detecting Straight Line Segments Using a Triangular Neighborhood

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Advances in Visual Computing (ISVC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6455))

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Abstract

A novel straight line segment detection method is proposed in this paper, based on the theory of mapping straight line segment neighborhoods between the image and the HT spaces and the geometrical analysis of the HT butterfly wings. This paper makes full use of the information in the butterfly wings to detect the segments, i.e. detecting segments by matching its butterfly wings. Due to the fact that the butterfly changes its shape and orientation according to the segment parameters, this paper deduces an approximation of the butterfly wings with triangles by moving and/or flipping the segments to the position that minimizes the approximating error. This movement alleviates the computation and precision loss introduced by the butterfly distortions, because straight side triangular regions can be used to obtain the parameters of segments. Compared to existing methods that detect segments using HT data, the proposed method utilizes more information around the butterfly center, and hence is more effective, especially when it is used to detect collinear segments. The experiments verify the performance of the proposed method.

This material is based upon work supported financially by the National Research Fundation (NRF) South Africa (Ref. IFR2010041400003). Any opinion, findings and conclusions or recommendations expressed in this material are those of authors and therefore the NRF does not accept any liability in regard thereto.

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Author information

Authors and Affiliations

  1. Department of Electrical and Mining Engineering, School of Engineering, College of Science Engineering and Technology, University of South Africa, Pretoria, 0003, South Africa

    Shengzhi Du

  2. French South Africa Technical Institute(FSATI), Tshwane University of Technology, Pretoria, 0001, South Africa

    Chunling Tu & Barend Jacobus van Wyk

Authors
  1. Shengzhi Du
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  2. Chunling Tu
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  3. Barend Jacobus van Wyk
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Ronald Chung

  6. Dyna Vox Systems, Pittsburgh, PA, USA

    Riad Hammound

  7. King Saud University, Riyadh, Saudi Arabia

    Muhammad Hussain

  8. Hewlett Packard Labs, Paolo Alto, CA, USA

    Tan Kar-Han

  9. The Ohio State University, Columbus, OH, USA

    Roger Crawfis

  10. Virtual Reality Lab, EPFL, Lausanne, Switzerland

    Daniel Thalmann

  11. NASA Ames Research Center, Clifton Park, NY, USA

    David Kao

  12. Kitware, Clifton Park, NY, USA

    Lisa Avila

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© 2010 Springer-Verlag Berlin Heidelberg

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Du, S., Tu, C., van Wyk, B.J. (2010). Detecting Straight Line Segments Using a Triangular Neighborhood. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_33

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  • DOI: https://doi.org/10.1007/978-3-642-17277-9_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17276-2

  • Online ISBN: 978-3-642-17277-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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