Automatic Road Detection in Grayscale Aerial Images

Digital aerial photography provides a useful starting point for computerized map generation. Features of interest can be extracted using a variety of image-processing techniques, which analyze the image for characteristics such as edges, texture, shape, and color. In this work, we develop an automatic road detection system for use on high-resolution grayscale aerial images. Road edges are extracted using a variant of the Nevatia-Babu edge detector. This is followed by an edge-thinning process and a new edgelinking algorithm that fills gaps in the extracted edge map. By using a zoned search technique, we are able to design an improved edge-linking algorithm that is capable of closing both large gaps in long, lowcurvature road edges and smaller gaps that can occur at triple points or intersection points. An edgepairing algorithm, which is subsequently applied, takes advantage of the parallel edges of roads to locate the road centers. Results demonstrate that the current system provides a simple yet effective first stage for a more sophisticated map-generation system.