The intelligence of the vehicle is identified by the surrounding environment. Lane detection is one of the vision-based features that used for assisting and controlling tasks for the intelligent vehicles. In this study, an overview of lane detection approaches is presented and then a model, based on inverse perspective mapping, edge detection and fitting lines algorithm is introduced. The system was tested on the urban road image data base in different light conditions. The performance of the system in term of lane marking detection was 97.2%. The results were accurate and robust with respect to the shadows and worn lane markings and also appropriate for real time procedure.
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