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An Approximation Algorithm for Computing Minimum-Length Polygons in 3D Images

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Computer Vision – ACCV 2010 (ACCV 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6495))

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Abstract

Length measurements in 3D images have raised interest in image geometry for a long time. This paper discusses the Euclidean shortest path (ESP) to be calculated in a loop of face-connected grid cubes in the 3D orthogonal grid, which are defined by minimum-length polygonal (MLP) curves. We propose a new approximation algorithm for computing such an MLP. It is much simpler and easier to understand and to implement than previously published algorithms by Li and Klette. It also has a straightforward application for finding an approximate minimum-length polygonal arc (MLA), a generalization of the MLP problem. We also propose two heuristic algorithms for computing a simple cube-arc within a 3D image component, with a minimum number of cubes between two cubes in this component. This may be interpreted as being an approximate solution to the general ESP problem in 3D (which is known as being NP-hard) assuming a regular subdivision of the 3D space into cubes of uniform size.

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Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Huaqiao University, Xiamen, Fujian, China

    Fajie Li & Xiuxia Pan

Authors
  1. Fajie Li
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  2. Xiuxia Pan
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Technion – Israel Institute of Technology, 32000, Haifa, Israel

    Ron Kimmel

  2. The University of Auckland, 37 Kohimarama Road, 1071, Mission Bay, Auckland, New Zealand

    Reinhard Klette

  3. National Institute of Informatics, 1018430, Chiyoda, Tokyo, Japan

    Akihiro Sugimoto

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Li, F., Pan, X. (2011). An Approximation Algorithm for Computing Minimum-Length Polygons in 3D Images. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19282-1_51

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  • DOI: https://doi.org/10.1007/978-3-642-19282-1_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19281-4

  • Online ISBN: 978-3-642-19282-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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