摘要
图形特征的变化是无穷的 ,只是依据与位移、夸大、化简等相似的综合方法 ,而不包含图形特征的识别与量测 ,数字海图的自动综合是无法实现的。只有识别、量测和综合方法的组合 ,才是数字海图综合概念的全部体现。因而 ,本文模拟人的综合方法的同时 ,重点模拟了人的图形特征的识别方式 ,同时 ,经过 Douglas二叉树方法的引入 ,给出了图形特征的识别与量测函数 ,实现了数字海图线性特征的自动综合。
Generalization is a comprehensive process. It is not simply a question of algorithm such as simplification, selection, displacement, etc. In addition, some of algorithms may fail to maintain consistent topological relations among features. Only after geometric shapes and topological properties have been understood fully, a sound and automated generalization process could be completed. This paper proposed a new theoretical model for generalization of all the line features in digital nautical chart. First, a binary tree structure, based on Douglas Peucker algorithm, is introduced for a hierarchical represent of line feature. Then, an analytical algorithm for the recognition of geometric shape and the measurement of the curvature of line features is developed by using the binary tree structure. An intelligent approach, used to identify and remove topological conflicts with line feature itself and all of its neighboring features, is given in this paper. Finally, all of the techniques mentioned above are integrated into a generalization model for all the line features, of which results are illustrated with the aid of several examples.
出处
《测绘学报》
EI
CSCD
北大核心
2000年第3期273-279,共7页
Acta Geodaetica et Cartographica Sinica
关键词
识别
量测
综合
线性特征
数字海图
海洋测量
recognition
measurement
generalization
line feature
digital nautical chart
