Abstract.
This article describes a method designed to detect and track road edges starting from images provided by an on-board monocular monochromic camera. Its implementation on specific hardware is also presented in the framework of the VELAC project. The method is based on four modules: (1) detection of the road edges in the image by a model-driven algorithm, which uses a statistical model of the lane sides which manages the occlusions or imperfections of the road marking – this model is initialized by an off-line training step; (2) localization of the vehicle in the lane in which it is travelling; (3) tracking to define a new search space of road edges for the next image; and (4) management of the lane numbers to determine the lane in which the vehicle is travelling. The algorithm is implemented in order to validate the method in a real-time context. Results obtained on marked and unmarked road images show the robustness and precision of the method.
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Received: 18 November 2000 / Accepted: 7 May 2001
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Aufrère, R., Chapuis, R. & Chausse, F. A model-driven approach for real-time road recognition. Machine Vision and Applications 13, 95–107 (2001). https://doi.org/10.1007/PL00013275
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DOI: https://doi.org/10.1007/PL00013275