ROAD EXTRACTION FOR THE UPDATE OF ROAD DATABASES IN SUBURBAN AREAS

This paper deals with road extraction in suburban areas from high resolution aerial images. The extraction results are intended to be used for updating a road database. The road extraction algorithm follows a region-based approach in which the image is first segmented using the normalized cuts algorithm with colour and edge criteria. Then, the initial segments are grouped to larger segments in order to overcome the oversegmentation which is a result of the first step. The segments are subsequently evaluated by shape criteria in order to extract road parts. Large segments that contain several roads are shaped irregularly; therefore, large segments are split prior to the road part extraction. The splitting is based on the skeleton of the segment. After the road part extraction, most roads in the image are covered by one extracted road part. However, some roads are covered by several road parts with gaps between them. In order to combine these road parts to one road, neighbouring road parts are connected if they have a similar main direction and a relatively high continuation smoothness. Results for some test images show that the approach is suitable for the extraction of roads in suburban images. * Corresponding author.