Detection of closed sharp edges in point clouds using normal estimation and graph theory

  • Authors:
  • Kris Demarsin;Denis Vanderstraeten;Tim Volodine;Dirk Roose

  • Affiliations:
  • Katholieke Universiteit Leuven, Department of Computer Science, Celestijnenlaan 200A, 3001 Heverlee, Belgium;Metris N.V., Interleuvenlaan 86, B-3001 Leuven, Belgium;Katholieke Universiteit Leuven, Department of Computer Science, Celestijnenlaan 200A, 3001 Heverlee, Belgium;Katholieke Universiteit Leuven, Department of Computer Science, Celestijnenlaan 200A, 3001 Heverlee, Belgium

  • Venue:
  • Computer-Aided Design
  • Year:
  • 2007

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Abstract

The reconstruction of a surface model from a point cloud is an important task in the reverse engineering of industrial parts. We aim at constructing a curve network on the point cloud that will define the border of the various surface patches. In this paper, we present an algorithm to extract closed sharp feature lines, which is necessary to create such a closed curve network. We use a first order segmentation to extract candidate feature points and process them as a graph to recover the sharp feature lines. To this end, a minimum spanning tree is constructed and afterwards a reconnection procedure closes the lines. The algorithm is fast and gives good results for real-world point sets from industrial applications.