• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>ISPRS (International Society for Photogrammetry and Remote Sensing) Workshop on Spatial Analysis and Decision Making; Dec 3-5, 2003; Hong Kong, China >Analysis and simplification of point cluster based on Delaunay triangulation model
【24h】

Analysis and simplification of point cluster based on Delaunay triangulation model

机译：基于Delaunay三角剖分模型的点聚类分析与简化

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Point cluster object contains much structured information in spatial distribution, which is interesting for the research of spatial analysis and map generalization. This paper divides the spatial distribution information of point cluster into three categories: existing, metrical structure and topological structure, and focuses the discussion on metrical structure. Based on the Delaunay triangulation and Voronoi diagram model, the paper defines four characteristic parameters for describing metrical structure: distribution range, distribution density, distribution centre and distribution axis. Considering Gestalt principles in visual adjacency cognition, the presented method finds the distribution range polygon by progressively stripping the outside triangles. The distribution density is represented by Voronoi cell size and visualized as a grey image. Applying an image processing method, the distribution centre can be extracted from the grey image. A method of point cluster simplification is provided in the paper on the basis of Voronoi diagram establishment in a dynamic way. The relative distribution properties above are preserved in the simplification method.
机译：点簇对象在空间分布中包含大量的结构化信息，这对于空间分析和地图概括的研究很有意义。本文将点簇的空间分布信息分为现存的，度量结构和拓扑结构三类，并将讨论重点放在度量结构上。基于Delaunay三角剖分和Voronoi图模型，本文定义了四个用于描述度量结构的特征参数：分布范围，分布密度，分布中心和分布轴。考虑到视觉邻接认知中的格式塔原理，提出的方法通过逐渐去除外部三角形来找到分布范围多边形。分布密度由Voronoi细胞大小表示，并可视为灰色图像。应用图像处理方法，可以从灰度图像中提取配送中心。本文在动态建立Voronoi图的基础上，提出了一种简化点聚类的方法。上述的相对分布特性在简化方法中得以保留。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号