Automatic road extraction based on cross detection in suburb

Abstract

Importance for acquiring geographic map data and updating existing data is increasing. The automation of road extraction from aerial imagery has received attention. In the past, many approaches have been considered, however the existing automatic road extraction methods still need too much post editing. In this paper, we propose the method of automatic road extraction from high-resolution color aerial images based on the information, such as a position and the direction of road intersection. As road shape recognition, we use an active contour model which is a kind of deformable shape model. The active contour model with a width parameter(called Ribbon Snakes) is useful as a technique to extract the road form, however the method has a problem how to generate a initial contour. We generate an initial contour using result of a road tracking. A road tracking is performed using the information, such as a position and the direction of road intersection. To detect road intersections, we use the template matching like cross form. We report experiments using high-resolution (0.5m per pixel) color aerial imagery of residential area in suburb.