利用四叉树在空间数据库中索引Voronoi单元格

Eriza Tri Abdi Nugroho, Kiki Adhinugraha, I. Asror
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引用次数: 2

摘要

计算几何是一门涉及到设计和分析解决几何问题的算法的数学知识领域。它可以应用于测绘、机器人、几何等领域。可以使用的一种方法是Voronoi图。Voronoi图是一种基于最近邻原则将区域划分为更小区域的方法。该方法仅适用于1阶voronoi图。在voronoi图中有一种新的变体,称为最高阶voronoi图(HSVD)。HSVD可用于所有顺序的voronoi图。然而,这些方法都存在着使用线性搜索来访问片段的缺点。从而使得数据片段查找区域的速度较慢,耗时较长。因此,本文将提出一种将最高阶Voronoi图纳入四叉树的索引结构。使用的四叉树索引能够切割一半以上的原始数据。该算法使搜索区域比以前更快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indexing Voronoi cells using quadtree in spatial database
Computational geometry is a mathematical knowlege in the field related to the design and analysis of algorithm to solve geometry problems. Its can be applicated in the fields of mapping, robotics, geometry and so forth. A method can be used is Voronoi diagram. Voronoi diagram is a method of deviding the area to a smaller area based on the principle of the nearest neighboring. This method only used in 1-order voronoi diagram. In voronoi diagram there is a new variation named Highest Order Voronoi Diagram (HSVD). HSVD can be used for all orders voronoi diagram. However, these methods have disadvantage that accessing fragment use linear search. Consequently make data fragment searches to find the region to be slow and takes a long time. Therefore, in this paper will present a index structure that incoperates Highest Order Voronoi Diagrams into Quadtree. Quadtree index used is capable of cutting more than half of the original data. This algorithm makes the search regions faster than before.
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