Advertisement

Machine Vision and Applications

, Volume 13, Issue 2, pp 95–107 | Cite as

A model-driven approach for real-time road recognition

  • Romuald Aufrère
  • Roland Chapuis
  • Frédéric Chausse
Original papers

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.

Key words: Lane recognition – Driving assistance – On-board systems – Real-time computer vision – Model-driven image analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Romuald Aufrère
    • 1
  • Roland Chapuis
    • 1
  • Frédéric Chausse
    • 1
  1. 1.LASMEA, UMR 6602 du CNRS, Université Blaise Pascal, 63177 Aubière Cedex, France; e-mail: {aufrere,chapuis,chausse}@lasmea.univ-bpclermont.fr, Tel.: +33-4-73407256, Fax: +33-4-73407262 FR

Personalised recommendations