三角剖分综述

多变形的三角剖分是计算几何中的基本问题,本文简述三角剖分的基本理论及应用,对三角剖分算法做简要的综述,为设计更好的三角剖分算法提供一定的依据。     

实现约束Delaunay三角剖分的健壮算法

相对于标准的Ｄｅｌａｕｎａｙ三角剖分，本文给出了复杂区域三角剖分所应满足的两个约束条件及相应的基于轨迹生成和边界裁剪的剖分算法，并证明了该算法符合约束圆准则，文中详细分析了退化及数值误差对剖分结果的影响，着重在提高算法健壮性方面，对该算法做了进一步完善，使它能够完全满足散乱据场网格剖分的分析。     

周培德三角剖分不是最小权三角剖分

平面点集的（欧几里德）最小权三角剖分问题是计算几何和算法领域的一个长期悬而未决的公开问题,周培德于文献[1]中提出了一个新的平面点集三角剖分算,并称该算法能够获得最小权三角剖分,文中通过给出反例,证明了该三角剖分不是最小权三角剖分,因此,最小权三角剖分问题仍有待于进一步研究。     

用随机增量局部转换算法实现三维点集的Delaunay三角剖分

Delaunay三角剖分作为计算几何中的一个核心问题,尤其适用于三维网格生成.因此就需要开发出高效、健壮性的算法来实现.本文在原有算法的基础上提出了随机增量局部转换的算法来实现三维点集的Delaunay三角剖分.采用不退化的四点生成最初的三角剖分,每次加入一点,通过局部交换使新的三角剖分保持Delaunay性质,直到处理完所有点.还讨论了局部交换的思想和对不同面类型的处理方法,给出了两个剖分实例.     

平面点集三角剖分的算法

提出平面点集三角剖分的一种新的算法，该算法首先逐层求凸包，然后分割环或成三角形，最后调整相邻环域的三角剖分便圾获得最小权三角剖分。     

曲面的自适应三角网格剖分

在传统的映射法基础上 ,采用自适应三角网格加密法能有效地处理带有特征约束条件的任意曲面的三角剖分问题 .在平面三角化算法中对环边统一处理 ,并且采取了一种简单有效的曲率估算方法 ,提高了运行效率 ;并在保持外观的基础上进行了网格质量的优化     

利用类Delaunay三角剖分实现Voronoi图

1引言 计算几何在计算机辅助设计、计算机图形学(特别是三维图形生成技术)及机器人等领域是非常重要的.特别在近年来,受到了学术界的极大关注.Voronoi图是计算几何的一个重要分支.在气象、生态、空中交通管制、城市规划等领域都得到广泛应用.     

基于Delaunay三角剖分生成Voronoi图算法

针对Delaunay三角网生长算法和间接生成Voronoi图算法构网效率不高的问题,提出了一种Delaunay三角网生长法间接生成Voronoi图的改进算法。该算法以点集凸壳上一边快速生成种子三角形,定义了半封闭边界点的概念,在三角形扩展过程中动态删除封闭点及半封闭边界点,加快Delaunay三角网生成速度。然后又定义了有序目标三角形的概念,该算法能迅速查找点的有序目标三角形,生成无射线的Voronoi图;考虑凸壳上点的特性,借助三个无穷点生成带射线的Voronoi图。通过实验结果分析表明,改进的算法执行效率有了很大提高。     

基于Delaunay与多边形三角剖分的印鉴识别算法

研究印鉴图像姿势纠正及印鉴匹配处理问题.在研究Delaunay三角剖分方法与多边形三角剖分方法的基础上,提出一种基于DT网格的印鉴识别方法.该方法通过对两种细节点(基于线条的细节点和基于多边形的细节点)的拓扑结构进行DT三角划分.用Delaunay三角剖分方法对基于线条的细节点集进行三角剖分,对基于多边形的细节点直接进行多边形三角剖分.通过对两种细节点的拓扑结构进行三角划分,把空间上位置相近的细节点按照三角剖分的规则相连,得到DT三角形网格.然后基于该网格寻找若干参考点对,并根据获得的参考点对将两幅印鉴图像进行姿势调整.实验结果表明该方法可以获得较多的参考点,确保印鉴旋转、印鉴平移等参数计算结果的准确性,有效提高最终的识别效果.     

基于MATLAB实现二维delaunay三角剖分

在已知凸多边形的顶点坐标的前提情况下,利用MATLAB中的meshgrid函数产生多边形附近矩形区域内的网格点的坐标,然后再利用inpolygon函数判断哪些点位于多边形内和哪些点位于多边形的边界上。在此基础上利用delaunay函数来完成delaunay三角剖分。     

Algorithm for constrained delaunay triangulation

A direct algorithm for computing constrained Delaunay triangulation in 2-D is presented. The algorithm inserts points along the constrained edges (break lines) to maintain the Delaunay criterion. Since many different insertions are possible, the algorithm computes only those that are on the Delaunay circles of each intersected triangle. A shelling procedure is applied to put triangles together in such a way that completeness and correctness are guaranteed.     

Point placement algorithms for Delaunay triangulation of polygonal domains

In some applications of triangulation, such as finite-element mesh generation, the aim is to triangulate a given domain, not just a set of points. One approach to meeting this requirement, while maintaining the desirable properties of Delaunay triangulation, has been to enforce the empty circumcircle property of Delaunay triangulation, subject to the additional constraint that the edges of a polygon be covered by edges of the triangulation. In finite-element mesh generation it is usually necessary to include additional points besides the vertices of the domain boundary. This motivates us to ask whether it is possible to trinagulate a domain by introducing additional points in such a manner that the Delaunay triangulation of the points includes the edges of the domain boundary. We present algorithms that given a multiply connected polygonal domain withN vertices, placeK additional points on the boundary inO(N logN + K) time such that the polygon is covered by the edges of the Delaunay triangulation of theN + K points. Furthermore,K is the minimum number of additional points such that a circle, passing through the endpoints of each boundary edge segment, exists that does not contain in its interior any other part of the domain boundary. We also show that by adding only one more point per edge, certain degeneracies that may otherwise arise can be avoided.     

An efficient sweep-line Delaunay triangulation algorithm

This paper introduces a new algorithm for constructing a 2D Delaunay triangulation. It is based on a sweep-line paradigm, which is combined with a local optimization criterion—a characteristic of incremental insertion algorithms. The sweep-line status is represented by a so-called advancing front, which is implemented as a hash-table. Heuristics have been introduced to prevent the construction of tiny triangles, which would probably be legalized. This algorithm has been compared with other popular Delaunay algorithms and it is the fastest algorithm among them. In addition, this algorithm does not use a lot of memory for supporting data structure, it is easy to understand and simple to implement.     

基于重新划分的三角形网格简化的一种改进算法

基于重新划分的三角形网格简化方法能自动生成多细节层次模型,它的基本思想是:根据三角形网格的局部几何和拓扑特征将一定数量的点分布到原网格上,生成一个中间网格,移去中间网格中的老顶点,并对产生的多边形区域进行局部三角化,最后形成以新点为顶点的三角形网格.本文在已有算法的基础上,提出了一种分布新点的算法,从而克服了原有方法的局限性.它利用三角形顶点的曲率和三角形的面积两个因素来反映网格在每个三角形处的特征.文中给出的一组实例说明了算法的有效性.     

三维任意区域中点集的三角剖分算法

本文在已有算法基础上，发展了一种三维任意区域中点集的三角剖分算法。该算法不仅可用于三维点集的标准Ｄｅｌａｕｎａｙ三角剖分，而且可用于带有约束表面及内部含有孔洞情况，可以处理非凸区域的三角剖分问题。算法对点在空间的位置滑任何限制。     

Computing the relative neighborhood graph in the L1 and L∞ metrics

The Relative Neighborhood Graph (RNG) of a set of nk-dimensional points connects “relatively close” neighbors: two points are connected by an edge if they are at least as close to each other as to any other point. Toussaint recently investigated the properties of the RNG in the Euclidean metric and proposed algorithms for its computation. This note examines one of the open problems listed by Toussaint: the extension of the analysis to non-Euclidean metrics. It is shown that Bentley's range query data structures may be used to improve the speed of the best known RNG algorithm in the L_∞ (for k ? 2) and L₁ (for k = 2) metrics.     

“The big sweep”: On the power of the wavefront approach to Voronoi diagrams

We show that the wavefront approach to Voronoi diagrams (a deterministic line-sweep algorithm that does not use geometric transform) can be generalized to distance measures more general than the Euclidean metric. In fact, we provide the first worst-case optimal (O (n logn) time,O(n) space) algorithm that is valid for the full class of what has been callednice metrics in the plane. This also solves the previously open problem of providing anO (nlogn)-time plane-sweep algorithm for arbitraryL _k -metrics. Nice metrics include all convex distance functions but also distance measures like the Moscow metric, and composed metrics. The algorithm is conceptually simple, but it copes with all possible deformations of the diagram. Research partially supported by the Natural Sciences and Engineering Research Council of Canada. Research partially supported by the Deutsche Forschungsgemeinschaft, Grant No. Kl 655/2-1.     

Duality of constrained Voronoi diagrams and Delaunay triangulations

We introduce theconstrained Voronoi diagram of a planar straight-line graph containingn vertices or sites where the line segments of the graph are regarded as obstacles, and show that an extended version of this diagram is the dual of theconstrained Delaunay triangulation. We briefly discussO(n logn) algorithms for constructing the extended constrained Voronoi diagram.This work was partially supported by a grant from the Natural Sciences and Engineering Research Council of Canada.     

An optimal speed-up parallel algorithm for triangulating simplicial point sets in space

Previous research on developing parallel triangulation algorithms concentrated on triangulating planar point sets.O(log³ n) running time algorithms usingO(n) processors have been developed in Refs. 1 and 2. Atallah and Goodrich⁽³⁾ presented a data structure that can be viewed as a parallel analogue of the sequential plane-sweeping paradigm, which can be used to triangulate a planar point set inO(logn loglogn) time usingO(n) processors. Recently Merks⁽⁴⁾ described an algorithm for triangulating point sets which runs inO(logn) time usingO(n) processors, and is thus optimal. In this paper we develop a parallel algorithm for triangulating simplicial point sets in arbitrary dimensions based on the idea of the sequential algorithm presented in Ref. 5. The algorithm runs inO(log² n) time usingO(n/logn) processors. The algorithm hasO(n logn) as the product of the running time and the number of processors; i.e., an optimal speed-up.