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Non-manifold Medial Surface Reconstruction from Volumetric Data

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Advances in Geometric Modeling and Processing (GMP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6130))

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Abstract

We present a method for medial surface reconstruction from volumetric data of thin-plate objects including junctions. Given medial voxels and distance fields computed from binarized volumes, we polygonize medial voxels by covering them with spherical supports and connecting the center points of the supports. These spherical supports are constructed by distributing spheres depending on the topological type of the voxels so that junction and boundary voxels are distributed first. Triangular meshes are built from Voronoi diagrams on medial voxels. This improvement builds correct junctions, whereas conventional voxel-based methods tend to result in small cavities around them. This paper also demonstrates several results computed from CT-scanned engineering objects.

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Author information

Authors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Takashi Michikawa & Hiromasa Suzuki

Authors
  1. Takashi Michikawa
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  2. Hiromasa Suzuki
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Editor information

Editors and Affiliations

  1. GALAAD, Inria Méditerannée, 2004 route des Lucioles, 06902, Sophia Antipolis Cedex, France

    Bernard Mourrain

  2. Department of Computer Science, College Station, Texas A&M University, 77843-3112, TX, USA

    Scott Schaefer

  3. Institute of Computational Mathematics and Scientific and Engineering Computing, Chinese Academy of Science, 100080, Beijing, China

    Guoliang Xu

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Michikawa, T., Suzuki, H. (2010). Non-manifold Medial Surface Reconstruction from Volumetric Data. In: Mourrain, B., Schaefer, S., Xu, G. (eds) Advances in Geometric Modeling and Processing. GMP 2010. Lecture Notes in Computer Science, vol 6130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13411-1_9

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  • DOI: https://doi.org/10.1007/978-3-642-13411-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13410-4

  • Online ISBN: 978-3-642-13411-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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