三维限定Voronoi网格剖分细化算法

针对分段线性复合形约束条件下的三维限定Voronoi剖分问题,提出一种细化算法.首先证明了分段线性复合形中的元素在最终生成的三维限定Voronoi网格中可表示为Power图结构;受此启发,提出了对限定线段平面片分别进行一维二维Power图细化以实现三维限定Voronoi 网格生成的细化算法,并且证明了该算法对于任意分段线性复合形收敛.最后通过实例验证了文中算法的有效性.     

改进的限定Voronoi图梯形检测带细分算法

针对已有的限定Voronoi图生成算法在一些复杂约束条件下不能收敛的问题,通过引入控制因子,给出一种 改进的限定Voronoi图梯形检测带细分算法。在计算初始Voronoi生长元的过程中,引入外部和内部限定线段端点 保护圆半径控制因子,控制限定线段两端点附近的Voronoi边的尺寸;在细分梯形检测带的过程中,引入外部和内部 限定线段尺寸控制因子,控制位于限定线段上的Voronoi边的尺寸。实验结果表明,本算法对于内部边界约束、线束 约束条件以及不规则区域均可以得到质量较好、满足约束条件的限定Voronoi图。     

二维约束Voronoi网格构造及其尺寸、质量控制

给出二维约束Voronoi网格的有关概念,分析了约束线段在二维Voronoi网格存在的条件,提出了一种二维约束Voronoi网格构造算法;并对二维约束Voronoi网格的尺寸和质量控制进行了研究;最后给出了实例以说明算法的有效性．该算法计算快速,适应性广,在诸多领域具有广泛的应用前景．     

三维约束Voronoi剖分

分析了约束面（点、线段、凸多边形）在三维Voronoi网格存在的条件,提出一种构造三维约束Voronoi剖分的算法．该算法的基本思想是在限定线的球覆盖基础上,借助限定面的约束Regular三角化生成关于限定面对称分布的生长点．理论上,对任意的分段线性复合形约束,该算法可以生成满足此约束的Voronoi网格．最后,给出了实例验证以说明文中算法的有效性．     

基于Voronoi 最小邻近点集的Delaunay 三角化方法

针对局部条件下网格生成的需求,提出一种基于节点的Delaunay 三角化 生成算法,该算法以Delaunay 三角形及其对偶Voronoi 图的局部性特征为基础,通过在局部 搜索最小Voronoi 邻近点集,来生成约束点附近的局部网格,通过建立背景索引网格,来提 高算法效率。给出算法的原理证明、程序实现、效率分析和测试结果,并给出了算法的应用 领域。     

基于Voronoi图的组最近邻查询

组最近邻查询由于涉及多个查询点,因此比传统的最近邻查询更为复杂.充分考虑查询点的分布特征以及它们构成的几何图形的性质和特点,给出组最近邻所应满足的条件及判断组最近邻的理论方法.提出基于Voronoi图的组最近邻查询的VGNN算法,可以精确求解查询点集的最近邻.对于查询点不共线的情况,该算法的查询方式是以一点为中心、向外扩张式的;对于查询点共线的情况,该算法给出搜索范围,限定了参与计算的数据点的个数.给出基于Voronoi图的VTree索引.实验结果表明,基于VTree索引的VGNN算法具有较好的性能,并且当查询点不共线时,其性能具有较高的稳定性.     

二维复杂限定Delaunay三角化算法

针对包括曲线边界和内部带有曲线限定条件的二维Delaunay三角化问题,提出了一种细化算法.首先给出了曲线段的逼近边定义,以保证限定曲线在网格中的存在;然后证明了该算法的收敛性和最终曲线的逼近边集合与原曲线的拓扑一致性,并且生成的网格符合Delaunay优化准则;最后给出了算法的应用实例,验证了其有效性.     

二维黎曼流形的Voronoi图生成算法

提出采用黎曼流形描述研究对象和基于坐标卡生成Voronoi图的算法思路.讨论了黎曼流形上研究Voronoi图的难点,并给出了存在定理,该定理说明了坐标卡上Voronoi图的存在条件.按照算法思路和存在定理,详细描述了二维黎曼流形上创建坐标卡的算法,并给出流形上转换函数和混合函数的定义方法.最后描述了基于坐标卡生成Voronoi图的算法,并给出了具体实例.     

对偶Voronoi聚类与重网格化

为了以更快的速度得到高质量的多分辨率网格,提出一种基于Voronoi-Delaunay三角化技术的多分辨率表示生成算法.该算法将原三角网格转化为对偶多边形网格再进行Voronoi划分,以自动满足共点聚类块不能超过3个这一约束;根据曲率分布情况来选取基点,以便能更好地捕捉几何特征;最后利用Loop细分规则与局部Laplace 平滑指导参数域上的重采样,再映射回模型空间获取最终采样结果,以提高重采样质量.由于Voronoi划分是重网格化算法的瓶颈,采用文中算法能减少划分时条件检测的耗时,从而显著地降低整个重网格化算法的时间复杂度.     

面向四面体网格生成的Delaunay refinement器官表面重建

为满足生物医学仿真系统对器官几何模型在Delaunay表面重构和四面体建模两方面的需求,提出一种面向四面体网格生成的Delaunay refinement表面重构算法.算法将从医学体数据中经过等值面提取和简化的初始表面作为输入和边界限定条件,为每个限定点计算局部特征尺寸并构建保护球,计算保护球与限定线段的交点并与限定点一起作为初始点集,生成Delaunay辅助四面体网格,引入一个迭代细分过程恢复边界,最终获得Delaunay重构表面.针对细分过程中的收敛性问题,文中给出了详细的理论证明和算法实例.此外,通过Delaunay四面体生成的对比实验表明该算法在Delaunay器官表面重构和四面体建模两方面兼具有效性和优越性.     

多尺度形态滤波及弹性匹配技术在类星体谱线识别中的应用

本文提出了一种类星体谱线证认方法。首先针对特征为极值点的信号，研究了多尺度膨胀（腐蚀）关于极值点数的两种重要特性及其应用。其一是单调率特性，根据它自动选择滤波器尺度，有效地滤除脉冲噪声；另一种是单调性，它是＂从粗到精＂策略来重新恢复极值特征位置的理论基础。根据这些性质，对光谱进行多尺度膨胀（腐蚀）和特征恢复，以滤除脉冲噪声而不影响谱线特征。然后研究弹性匹配技术应用于谱线证认，并指出了匹配方法中参量的物理意义。该方法对其他一些应用领域也行之有效     

Hexahedral Mesh Generation using the Embedded Voronoi Graph

This work presents a new approach for automatic hexahedral meshing, based on the embedded Voronoi graph. The embedded Voronoi graph contains the full symbolic information of the Voronoi diagram and the medial axis of the object, and a geometric approximation to the real geometry. The embedded Voronoi graph is used for decomposing the object, with the guiding principle that resulting sub-volumes are sweepable. Sub-volumes are meshed independently, and the resulting meshes are easily combined and smoothed to yield the final mesh. The approach presented here is general and automatic. It handles any volume, even if its medial axis is degenerate. The embedded Voronoi graph provides complete information regarding proximity and adjacency relationships between the entities of the volume. Hence, decomposition faces are determined unambiguously, without any further geometric computations. The sub-volumes computed by the algorithm are guaranteed to be well-defined and disjoint. The size of the decomposition is relatively small, since every sub-volume contains a different Voronoi face. Mesh quality seems high since the decomposition avoids generation of sharp angles, and sweep and other basic methods are used to mesh the sub-volumes.     

Guaranteed-quality anisotropic mesh generation for domains with curved boundaries

Anisotropic mesh generation is important for interpolation and numerical modeling. Recently, Labelle and Shewchuk proposed a two-dimensional guaranteed-quality anisotropic mesh generation algorithm called a Voronoi refinement algorithm. This algorithm treats only domains with straight lines as inputs. In many applications, however, input domains have many curves and the exact representation of curves is required for efficient numerical modeling. In this paper, we extend the Voronoi refinement algorithm and propose it as a guaranteed-quality anisotropic mesh generation algorithm for domains with curved boundaries. Some experimental results are also shown.     

Efficient Generation of Conforming Voronoi Polygonal Surface Mesh

A novel construction algorithm is presented to generate a conforming Voronoi mesh for any planar straight line graph (PSLG). It is also extended to tesselate multiple-intersected PSLGs. All the algorithms are guaranteed to converge. Examples are given to illustrate its efficiency.     

Polyline‐sourced Geodesic Voronoi Diagrams on Triangle Meshes

This paper studies the Voronoi diagrams on 2‐manifold meshes based on geodesic metric (a.k.a. geodesic Voronoi diagrams or GVDs), which have polyline generators. We show that our general setting leads to situations more complicated than conventional 2D Euclidean Voronoi diagrams as well as point‐source based GVDs, since a typical bisector contains line segments, hyperbolic segments and parabolic segments. To tackle this challenge, we introduce a new concept, called local Voronoi diagram (LVD), which is a combination of additively weighted Voronoi diagram and line‐segment Voronoi diagram on a mesh triangle. We show that when restricting on a single mesh triangle, the GVD is a subset of the LVD and only two types of mesh triangles can contain GVD edges. Based on these results, we propose an efficient algorithm for constructing the GVD with polyline generators. Our algorithm runs in O(nNlogN) time and takes O(nN) space on an n‐face mesh with m generators, where N = max{m, n}. Computational results on real‐world models demonstrate the efficiency of our algorithm.     

散乱点的快速曲面重建方法

空间散乱点的曲面重建有着广泛的应用前景，是当前国际上的研究热点之一，Crust算法是一种基于计算几何中的Voronoi周期图的曲面重建算法，它算法简单，重建结果精细，但是由于计算量太大，其应用受到了限制，为此提出了一种依据采样点的局部特征尺度对原始采样集进行不均匀降采样的方法，在保证采样集能够满足重建要求的前提下，使参与重建的表面点数大为降低，减少了重建算法的计算量，从而提高了重建的速度，这一方法还可以应用于网络简化，通过剔除某些顶点达到简化之目的。     

Isotropic Remeshing with Fast and Exact Computation of Restricted Voronoi Diagram

We propose a new isotropic remeshing method, based on Centroidal Voronoi Tessellation (CVT) . Constructing CVT requires to repeatedly compute Restricted Voronoi Diagram (RVD) , defined as the intersection between a 3D Voronoi diagram and an input mesh surface. Existing methods use some approximations of RVD. In this paper, we introduce an efficient algorithm that computes RVD exactly and robustly. As a consequence, we achieve better remeshing quality than approximation-based approaches, without sacrificing efficiency. Our method for RVD computation uses a simple procedure and a kd -tree to quickly identify and compute the intersection of each triangle face with its incident Voronoi cells. Its time complexity is O ( m log n ), where n is the number of seed points and m is the number of triangles of the input mesh. Fast convergence of CVT is achieved using a quasi-Newton method, which proved much faster than Lloyd's iteration. Examples are presented to demonstrate the better quality of remeshing results with our method than with the state-of-art approaches.