Feature-preserving anisotropic smoothing for meshes with large-scale noise

Masatake Higashi, Tetsuo Oya, Tetsuro Sugiura, Masakazu Kobayashi

研究成果: Article査読

抄録

This paper presents a smoothing method which preserves features for a triangular mesh even when large-scale noise are included because of measurement errors. First, scale-dependent discrete Laplacian is introduced along with boundary Laplacian to deal with an open mesh. Then, a method for feature detection which uses the values by these Laplacians is constructed. Furthermore, anisotropic diffusion is proposed which determines suitable parameters from the values for preserving features. Finally a method is presented which discriminates features from large-scale noise by generating graph of feature lines. Effectiveness of the methods is shown by the experiment results of well-smoothed meshes with their features preserved.

本文言語English
ページ(範囲)365-374
ページ数10
ジャーナルComputer-Aided Design and Applications
6
3
DOI
出版ステータスPublished - 2009
外部発表はい

ASJC Scopus subject areas

  • 計算力学
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • 計算数学

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