Roads Detection from Satellite Images Based on Active Contour Model and Distance Transform

Automatic man-made objects detection from aerial and satellite images be a very important research field to understand the changes in our environment and gives an important source of information to be used in many fields. This study describes and evaluates an automated method for roads detection using a region-based active contour model and distance transform. The first step is pre-processing of images to reduce noses and increase the contrast between contours and to improve the quality of the initial image by using the median filtering, the second step deals with using an active contour with a region-based signed pressure force (SPF) function that is adapted with the given images and in the last step centerlines of road are extracted with Euclidian distance transformation. The proposed method is tested on several images with high resolution and experiments results show that can detect both urban and suburban roads.