CVT-based 3D image segmentation and quality improvement of tetrahedral/hexahedral meshes using anisotropic Giaquinta-Hildebrandt operator
CVT-based 3D image segmentation and quality improvement of tetrahedral/hexahedral meshes using anisotropic Giaquinta-Hildebrandt operator
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DOI：
10.1080/21681163.2016.1244017
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Kangkang Hu;Y. Zhang;Guoliang Xu
中科院分区：
文献类型：
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作者：
Kangkang Hu;Y. Zhang;Guoliang Xu
给定一幅输入的三维图像，本文首先将二维调和边缘加权质心Voronoi曲面细分方法推广到三维图像域，将其分割成若干簇。然后应用对偶轮廓法，通过分析材料变化边和内部边来构造四面体网格。六面体网格也可以通过分析每个内部网格点来生成。提出了一种基于各向异性Giaquinta-Hildebrandt算子的几何流方法，该方法能在保持体特征和表面特征的情况下实现曲面的光顺。优化为基础的平滑和拓扑优化也适用于提高质量的四面体和六面体网格。我们已经验证了我们的算法，将它们应用到几个数据集。
Given an input three-dimensional (3D) image in this paper, we first segment it into several clusters by extending the two-dimensional harmonic edge-weighted centroidal Voronoi tessellation method to the 3D image domain. The dual contouring method is then applied to construct tetrahedral meshes by analysing both material change edges and interior edges. Hexahedral meshes can also be generated by analysing each interior grid point. An anisotropic Giaquinta–Hildebrandt operator-based geometric flow method is developed to smooth the surface with both volume and surface features preserved. Optimisation-based smoothing and topological optimisations are also applied to improve the quality of tetrahedral and hexahedral meshes. We have verified our algorithms by applying them to several data-sets.