Road network extraction from high resolution satellite images

作     者：Li Gang Lai Shunnan Li Sheng 

作者机构：Peking University Shenzhen Graduate School Shenzhen 518055 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Beijing 100871 China 

基　　金：Supported by National Natural Science Foundation of China(NSFC)(61232014,61421062,61472010) National Key Technology R&D Program of China(2015BAK01B06) 

出 版 物：《Computer Aided Drafting,Design and Manufacturing》 (计算机辅助绘图设计与制造（英文版）)

年 卷 期：2016年第26卷第2期

页      码：1-7页

摘      要：In this paper, an approach of roads network extraction from high resolution satellite images is presented. First, the approach extracts road surface from satellite image using one-class support vector machine （SVM）. Second, the road topology is built from the road surface. The last output of the approach is a series of road segments which is represented by a sequence of points as well as the topological relations among them. The approach includes four steps. In the first step one-class support vector machine is used for classifying pixel of the satellite images to road class or non-road class. In the second step filling holes and connecting gaps for the SVM＇s classification result is applied through mathematical morphology close operation. In the third step the road segment is extracted by a series of operations which include skeletonization, thin, branch pruning and road segmentation. In the last step a geometrical adjustment process is applied through analyzing the road segment curvature. The experiment results demonstrate its robustness and viability on extracting road network from high resolution satellite images.

主 题 词：road extraction topology mathematical morphology skeletonization support vector machine 

学科分类：0810[工学-土木类] 08[工学] 081002[081002] 

D　O　I：10.19583/j.1003-4951.2016.02.001

馆 藏 号：203210333...