Road-Following and Traffic Analysis using High-Resolution Remote Sensing Imagery

As vehicle population increases, ITS (Intelligent Transportation Systems) becomes more significant and mandatory in today's overpopulated world. Vital problems in transportation such as mobility and safety of transportation are considered more, especially in metropolitans and road ways. Road traffic monitoring aims at the acquisition and analysis of traffic figures, such as presence and numbers of vehicles, and automatic driver warning systems are developed mainly for localization and safety purposes. In this paper we propose a strategy for road following from aerial images. Real time extraction and localization of a road from an aerial image is an emerging research area that can be applied to vision-based traffic controlling and navigation of unmanned air vehicles. In order to deal with the high complexity of this type of images, we integrate detailed knowledge about roads using explicitly formulated scale-dependent models. The intensity images are used for the extraction of road from aerial images. Threshold techniques, Hough transform and learning algorithm are used for the road extraction and car detection. The results show that the proposed approach has a good detection performance.