Utilizing Road Network Data for Automatic Identification of
ABSTRACT Recent growth of the geo-spatial information on the web has made it possible to easily access various and high quality geo-spatial datasets, such as road networks and high resolution imagery. Although there exist efficient methods to locate road intersections from road networks for route planning, there are few research activities on detecting road intersections from orthoimagery. Detected road intersections on imagery can be utilized for conflation, cityplanning and other GIS-related applications. In this paper, we describe an approach to automatically and accurately identifying road intersections from high resolution color orthoimagery. We exploit image metadata as well as the color of imagery to classify the image pixels as on-road/off-road. Using these chromatically classified image pixels as input, we locate intersections on the images by utilizing the knowledge inferred from the road network.