Frank C Langbein
Ex Tenebris Scientia
Contents

F. C. Langbein, B. I. Mills, A. D. Marshall, R. R. Martin.

J. Computing and Information Science in Engineering, 1(4): 282-290, 2001.
ISSN 15309827.

[DOI: 10.1115/1.1430232] [Preprint]

Current reverse engineering systems can generate boundary representation (B-rep) models from 3D range data. Such models suffer from inaccuracies caused by noise in the input data and algorithms. The quality of reverse engineered geometric models can be improved by finding candidate shape regularities in such a model, and constraining the model to meet a suitable subset of them, in a post-processing step called beautification. This paper discusses algorithms to detect such approximate regularities in terms of similarities between feature objects describing properties of faces, edges and vertices, and small groups of these elements in a B-rep model with only planar, spherical, cylindrical, conical and toroidal faces. For each group of similar feature objects they also seek special feature objects which may represent the group, e.g. an integer value which approximates the radius of similar cylinders. Experiments show that the regularities found by the algorithms include the desired regularities as well as spurious regularities, which can be limited by an appropriate choice of tolerances.

@ARTICLE{Langbein2001b,
  author =       {Frank C. Langbein and Bruce I. Mills and A. Dave
                  Marshall and Ralph R. Martin},
  title =        {Finding Approximate Shape Regularities for Reverse
                  Engineering},
  journal =      {Journal of Computing and Information Science in
                  Engineering},
  year =         2001,
  volume =       1,
  pages =        {282-290},
  number =       4,
  month =        {December},
  issn =         15309827,
  doi =          {10.1115/1.1430232},
  url =          {http://www.langbein.org/research/solids/borg/langbein2001b/},
  abstract =     {Current reverse engineering systems can generate
                  boundary representation (B-rep) models from 3D range
                  data. Such models suffer from inaccuracies caused by
                  noise in the input data and algorithms. The quality
                  of reverse engineered geometric models can be
                  improved by finding candidate shape regularities in
                  such a model, and constraining the model to meet a
                  suitable subset of them, in a post-processing step
                  called beautification. This paper discusses
                  algorithms to detect such approximate regularities
                  in terms of similarities between feature objects
                  describing properties of faces, edges and vertices,
                  and small groups of these elements in a B-rep model
                  with only planar, spherical, cylindrical, conical
                  and toroidal faces. For each group of similar
                  feature objects they also seek special feature
                  objects which may represent the group, e.g. an
                  integer value which approximates the radius of
                  similar cylinders. Experiments show that the
                  regularities found by the algorithms include the
                  desired regularities as well as spurious
                  regularities, which can be limited by an appropriate
                  choice of tolerances.},
}
Cite as Finding Approximate Shape Regularities for Reverse Engineering, http://www.langbein.org/research/solids/borg/langbein2001b/ by Frank C Langbein [27/October/2008, 21:27].
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