Lane detection using spline model
Pattern Recognition Letters
A Lane Departure Warning System Based on Machine Vision
PACIIA '08 Proceedings of the 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application - Volume 01
A Method for Lane Detection Based on Color Clustering
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Robust lane detection and tracking with RANSAC and Kalman filter
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Model-Based Lane Detection and Lane Following for Intelligent Vehicles
IHMSC '10 Proceedings of the 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 02
A comparative study of vision-based lane detection methods
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Lane Detection With Moving Vehicles in the Traffic Scenes
IEEE Transactions on Intelligent Transportation Systems
An Improved Lane Detection and Tracking Method for Lane Departure Warning Systems
International Journal of Computer Vision and Image Processing
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In driver assistance systems, lane detection and tracking are very crucial treatments to locate the vehicle and to track its position on the road. The aim of this study is to propose lane detection and tracking method. The first step in this method detects road limits on the first acquired image. The detected limits would be the input for the second step, namely the "tracking step", which consists in providing a continuous detection of the limits in all frames by updating the previously detected limits. Lane departure is also analyzed for the lateral control of the vehicle. The approach presented here was tested on video sequences filmed by the authors on Tunisian roads, on a video sequence provided by Daimler AG as well as on the PETS2001 dataset provided by the Essex University.