Automatic vectorization of segmented road networks by geometrical and topological analysis of high resolution binary images

作者:

Highlights:

摘要

In this paper, a new method in order to achieve the geometrical and topological definition of extracted road networks is presented. Starting from a raster binary image where a road network is depicted, this algorithm seeks the automatic raster – vector conversion based on skeleton extraction and graph theory and using GIS database if it is available. The last goal of this method is to provide a numerical structured file which includes the geometric definition for all roads as well as the topologic relations between them. The applied technique comprises six steps. In the first step, the quality of the binary image is improved through a noise cleaning process. In the second step, parallel edges of road network are smoothed by means a generalization process. In the third step, skeleton is extracted applying a known and efficient method which some years ago was published. The fourth step consists in constructing the graph and generating the different cartographic objects which compose the road network. In this phase, GIS information can be used in order to improve the result. In the fifth step, objects are numerically adjusted by means of polynomial adjustment in the opened objects case, and using a reiterative polygonal adjustment in the sharp objects case. In the last step, mathematical morphology is applied to validate topologically the geometrical adjustment. For it, the junction nodes are analyzed for changing automatically their coordinates in order to achieve a topologically correct road network vectorization. Finally, objects are structured according to cartographic criteria and a numerical file with the vectorized road network is provided. Experimental results show the validity of this approach.

论文关键词:Skeleton,Graph,Adjustment,Topology,Road extraction,GIS data,Vectorization

论文评审过程:Received 21 April 2004, Accepted 4 May 2006, Available online 13 July 2006.

论文官网地址:https://doi.org/10.1016/j.knosys.2006.05.008