Automatic extractions of road intersections from satellite imagery in urban areas

Information of the urban road areas for resource management, security monitoring, urban development and Geographic Information System (GIS) is changing with the growing world. Satellite image provides useful data that is extracted from satellite image of the urban area. Automatic extraction of the road intersections from the urban areas has been a challenging topic because the high resolution satellite images contain multiple layers that represent roads, buildings, and other high density objects. Our goals is to automatically separate the road layer from the other layers then extract the road intersections. Usually traditional image processing methods don't achieve satisfied performance in case of satellite images. In this paper we propose a cost effective method for road extraction from Satellites images. In order to find the precise road intersection of urban areas we have divided that whole process into two sequential modules: first, extraction of road line using different Morphological direction filtering to automatically eliminate the other layers from road layer and finally, extraction of road intersections to determine the road orientation and interconnectivity. For our proposed Road intersection extraction, we applied the method to a set of randomly selected satellite image from urban and semi urban areas and achieved over 95.8% precision.