Road Segmentation in Aerial Images by Exploiting Road Vector Data

Abstract

Segmenting road regions from high resolution aerial images is an important yet challenging task due to large variations on road surfaces. This paper presents a simple and effective method that accurately segments road regions with a weak supervision provided by road vector data, which are publicly available. The method is based on the observation that in aerial images road edges tend to have more visible boundaries parallel to road vectors. A factorization-based segmentation algorithm is applied to an image, which accurately localize boundaries for both texture and nontexture regions. We analyze the spatial distribution of boundary pixels with respect to the road vector, and identify the road edge that separates roads from adjacent areas based on the distribution peaks. The proposed method achieves on average 90% recall and 79% precision on large aerial images covering various types of roads.