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A voronoi based labeling approach to curve reconstruction and medial axis approximation

  • Advanced Geometric Computing Lab
  • Indian Institute of Technology Madras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

In this paper, we present a Voronoi based algorithm for closed curve reconstruction and medial axis approximation from planar points. In principle, the algorithm estimates one of the poles (farthest Voronoi vertices of a Voronoi cell) and hence the normals at each sample point by drawing an analogy between a residential water distribution system and Voronoi diagram of input samples. The algorithm then labels Voronoi vertices as either inner or outer with respect to the original curve and subsequently construct a piece-wise linear approximation to the boundary and the interior medial axis of the original curve for a class of curves having bi-tangent neighborhood convergence (BNC). The proposed algorithm has been evaluated for its usefulness using various test data. Results indicate that, even sparsely and non-uniformly sampled curves with sharp corners, outliers or collection of curves are faithfully reconstructed by the proposed algorithm.

Original languageEnglish
Title of host publication23rd Pacific Conference on Computer Graphics and Applications, PG 2015 - Short Papers Proceedings
EditorsNiloy J. Mitra, Jos Stam, Kun Xu
PublisherIEEE Computer Society
Pages77-82
Number of pages6
ISBN (Electronic)9783905674965
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event23rd Pacific Conference on Computer Graphics and Applications, PG 2015 - Short Papers - Beijing, China
Duration: 7 Oct 2015 → 9 Oct 2015

Publication series

NameProceedings - Pacific Conference on Computer Graphics and Applications
Volume2015-October
ISSN (Print)1550-4085

Conference

Conference23rd Pacific Conference on Computer Graphics and Applications, PG 2015 - Short Papers
Country/TerritoryChina
CityBeijing
Period7/10/15 → 9/10/15

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