Bi-Normal Mesh Smoothing Based on Vertex Feature
Aiming at the issue that mesh smoothing is hard to balance in terms of noise removing and feature preserving, in this article, we combine the facet normal representing global geometric features of the mesh with the vertex normal characterizing local details of the mesh and propose a bi-normal mesh s...
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doaj-dfa50f582df04b74b4dfc5802dc9a8552021-03-30T03:59:09ZengIEEEIEEE Access2169-35362020-01-01817146917147810.1109/ACCESS.2020.30226289187871Bi-Normal Mesh Smoothing Based on Vertex FeatureWuli Wang0https://orcid.org/0000-0003-0688-0961Liming Duan1https://orcid.org/0000-0001-7441-5266College of Oceanography and Space Informatics, China University of Petroleum, Qingdao, ChinaEngineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing, ChinaAiming at the issue that mesh smoothing is hard to balance in terms of noise removing and feature preserving, in this article, we combine the facet normal representing global geometric features of the mesh with the vertex normal characterizing local details of the mesh and propose a bi-normal mesh smoothing method based on vertex feature selection (BNBVF). Firstly, the guided filtering algorithm is extended to calculate accurately the facet normal in the field of geometric processing. The key of this portion is computing the guided normal of facet by using a geometric neighboring patch with the most consistent normal. Then, an adaptive tensor voting method is employed to divide the vertices of the mesh into feature vertices and non-feature vertices. Thirdly, a method of the neighborhood facets clustering combining with the plane fitting is proposed to calculate the normal of feature vertex, and the weighting average of first-order neighborhood facets of the vertex is applied to compute the normal of non-feature vertex. Finally, the vertices of the mesh are updated iteratively by combining the geometric information of the facet normal and vertex normal to achieve mesh smoothing. Experimental results demonstrate that the superior performance of our proposed algorithm to state-of-the-art approaches in feature preserving and error reducing.https://ieeexplore.ieee.org/document/9187871/Mesh smoothingfeature-preservingbi-normalguided filteringtensor voting |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wuli Wang Liming Duan |
spellingShingle |
Wuli Wang Liming Duan Bi-Normal Mesh Smoothing Based on Vertex Feature IEEE Access Mesh smoothing feature-preserving bi-normal guided filtering tensor voting |
author_facet |
Wuli Wang Liming Duan |
author_sort |
Wuli Wang |
title |
Bi-Normal Mesh Smoothing Based on Vertex Feature |
title_short |
Bi-Normal Mesh Smoothing Based on Vertex Feature |
title_full |
Bi-Normal Mesh Smoothing Based on Vertex Feature |
title_fullStr |
Bi-Normal Mesh Smoothing Based on Vertex Feature |
title_full_unstemmed |
Bi-Normal Mesh Smoothing Based on Vertex Feature |
title_sort |
bi-normal mesh smoothing based on vertex feature |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Aiming at the issue that mesh smoothing is hard to balance in terms of noise removing and feature preserving, in this article, we combine the facet normal representing global geometric features of the mesh with the vertex normal characterizing local details of the mesh and propose a bi-normal mesh smoothing method based on vertex feature selection (BNBVF). Firstly, the guided filtering algorithm is extended to calculate accurately the facet normal in the field of geometric processing. The key of this portion is computing the guided normal of facet by using a geometric neighboring patch with the most consistent normal. Then, an adaptive tensor voting method is employed to divide the vertices of the mesh into feature vertices and non-feature vertices. Thirdly, a method of the neighborhood facets clustering combining with the plane fitting is proposed to calculate the normal of feature vertex, and the weighting average of first-order neighborhood facets of the vertex is applied to compute the normal of non-feature vertex. Finally, the vertices of the mesh are updated iteratively by combining the geometric information of the facet normal and vertex normal to achieve mesh smoothing. Experimental results demonstrate that the superior performance of our proposed algorithm to state-of-the-art approaches in feature preserving and error reducing. |
topic |
Mesh smoothing feature-preserving bi-normal guided filtering tensor voting |
url |
https://ieeexplore.ieee.org/document/9187871/ |
work_keys_str_mv |
AT wuliwang binormalmeshsmoothingbasedonvertexfeature AT limingduan binormalmeshsmoothingbasedonvertexfeature |
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1724182569628467200 |