Automatic extraction of road intersections from raster maps

Numerous raster maps are available on the Internet, but the geographic coordinates of the maps are often unknown. In order to determine the precise location of a raster map, we exploit the fact that the layout of the road intersections within a certain area can be used to determine the map's location. In this paper, we describe an approach to automatically extract road intersections from arbitrary raster maps. Identifying the road intersections is difficult because raster maps typically contain multiple layers that represent roads, buildings, symbols, street names, or even contour lines, and the road layer needs to be automatically separated from other layers before road intersections can be extracted. We combine a variety of image processing and graphics recognition methods to automatically eliminate the other layers and then extract the road intersection points. During the extraction process, we determine the intersection connectivity (i.e., number of roads that meet at an intersection) and the road orientations. This information helps in matching the extracted intersections with intersections from known sources (e.g., vector data or satellite imagery). For the problem of road intersection extraction, we applied the techniques to a set of 48 randomly selected raster maps from various sources and achieved over 90% precision with over 75% recall. These results are sufficient to automatically align raster maps with other geographic sources, which makes it possible to determine the precise coverage and scale of the raster maps.