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

Masatake Higashi, Tetsuo Oya, Tetsuro Sugiura, Masakazu Kobayashi

研究成果: Article

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.

元の言語English
ページ(範囲)365-374
ページ数10
ジャーナルComputer-Aided Design and Applications
6
発行部数3
DOI
出版物ステータスPublished - 2009
外部発表Yes

Fingerprint

Measurement errors
Smoothing
Mesh
Discrete Laplacian
Feature Detection
Anisotropic Diffusion
Smoothing Methods
Triangular Mesh
Experiments
Measurement Error
Dependent
Line
Graph in graph theory
Experiment

ASJC Scopus subject areas

  • Computational Mechanics
  • Computer Graphics and Computer-Aided Design
  • Computational Mathematics

これを引用

Feature-preserving anisotropic smoothing for meshes with large-scale noise. / Higashi, Masatake; Oya, Tetsuo; Sugiura, Tetsuro; Kobayashi, Masakazu.

:: Computer-Aided Design and Applications, 巻 6, 番号 3, 2009, p. 365-374.

研究成果: Article

Higashi, Masatake ; Oya, Tetsuo ; Sugiura, Tetsuro ; Kobayashi, Masakazu. / Feature-preserving anisotropic smoothing for meshes with large-scale noise. :: Computer-Aided Design and Applications. 2009 ; 巻 6, 番号 3. pp. 365-374.
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