Roads Extraction and Mapping from Aerial and Satellite Images

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 as an infrastructure, mapping generation, planning traffics and cartographic. This study describes and evaluates an automated method for roads extraction and mapping. For roads extraction we follow these steps: 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 bilateral filtering, the second step deals with Statistical Region Merging to segment the image into homogenous regions, in the third step roads are detected based on modified active contour with adaptive initial contour to localize the region of road followed by edge detection and linking. For road centerlines extraction and mapping, skeleton centerlines of roads were calculated by using the fast-marching distance transform. The proposed method is tested on several images with high resolution and experiments results show that can extract and map roads with a better accuracy of 93.36%.