中文摘要：

提出一种结合纹理和形状特征提取道路信息的方法。首先利用灰度共生矩阵提取纹理特征,并将其应用于最大似然分类中提取面状道路,然后利用形态学方法分割道路与其相连地物,最后利用提出的3个形状指数（凹度、精密度、偏心角）有效地识别和区分了道路与非道路地物,并最终实现了提纯道路的目的。实验结果证明,该方法可以准确地提取主干道路网,剔除非道路地物的影响。

英文摘要：

As one of the most important features in geographic database,road extraction is always the research focus in the field of remote sensing.This paper proposes a new method integrating texture and shape features for road extraction.Firstly,the texture feature obtained by gray-level co-occurrence matrix（GLCM） is applied to maximum likelihood classification and to extract the road surface image;then the morphological methods are utilized to segment the road and non-road objects;finally,three shape features are presented to refine the road information and eliminate the influence of non-road objects,such as buildings and parking lots.Experimental results indicate that this method is efficient to extract the central road network accurately.