随机点群目标空间图形的表达与识别

The representation and identification of spatial graphics for random point cluster

本文针对国内外一些对点群目标的自动综合方法中存在的弊端,提出了一种新的自动综合模式———空间图形的表达、识别与综合。通过在点群中构建Delaunay三角网,并加入相应的约束条件,实现对随机点群目标空间图形的表达。从外围轮廓,内部结构,中轴线的提取和单个点目标的影响域几方面对点群目标的综合参数进行了识别。表达与识别为地图自动综合的实施奠定了基础。这一方法必将提高综合的自动化程度,成为自动综合研究领域中一个新的突破点。

This paper analyzed some automatic generalization of point cluster and put forward a new pattern which is representing,identifying and generalizing spatial graph.To realize representation,it is necessaty to build Delaunay triangular network with some conditions.The identification of generalization parameter includes outline,inside structure,center-axis and the extension of point.Representation and identification is the basis of map automatic generalization.This may improve the degree of automatic generalization,and will become a new viewpoint in the field of automatic generalization.