Multi-lane detection in urban driving environments employing omni-directional camera

Lane detection is crucial part of vision driver assistance system of intelligent vehicles. In this paper we present a multi-lane detection method using omni-directional camera. The contribution of this paper is twofold. Firstly, we present an anisotropy steerable filter with the aim of get more reliable lane markings feature extraction under adverse circumstance. Secondly, an optimization method to fit the parameter of lane model is proposed. The proposed method is tested on different road images taken by omni-directional camera. Experimental results indicate the good performance of the proposed method.

[1]  Rama Chellappa,et al.  A Learning Approach Towards Detection and Tracking of Lane Markings , 2012, IEEE Transactions on Intelligent Transportation Systems.

[2]  K. Watanabe,et al.  Lane detection for intelligent vehicle employing omni-directional camera , 2004, SICE 2004 Annual Conference.

[3]  Ronen Lerner,et al.  Recent progress in road and lane detection: a survey , 2012, Machine Vision and Applications.

[4]  Kajiro Watanabe,et al.  Lane detection by using omni-directional camera for outdoor terrains , 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

[5]  Ying Lin,et al.  Stereo Calibration and Rectification for Omnidirectional Multi-Camera Systems , 2012 .

[6]  Mohan M. Trivedi,et al.  Lane Tracking with Omnidirectional Cameras: Algorithms and Evaluation , 2007, EURASIP J. Embed. Syst..

[7]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Pierre Charbonnier,et al.  Evaluation of Road Marking Feature Extraction , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[9]  Hsu-Yung Cheng,et al.  Lane Detection With Moving Vehicles in the Traffic Scenes , 2006, IEEE Transactions on Intelligent Transportation Systems.

[10]  Franz Kummert,et al.  Spatial ray features for real-time ego-lane extraction , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.