Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dai, X., Kummert, A., Park, S.B., Neisius, D.: A warning algorithm for lane departure warning system. In: IEEE Intelligent Vehicles Symposium (2009)
Yu, B., Zhang, W., Cai, Y.: A Lane Departure Warning System based on Machine Vision. In: IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application (2008)
Assidiq, A., Khalifa, O., Islam, R., Khan, S.: Real Time Lane Detection for Autonomous Vehicles. In: Int. Conf. on Computer and Communication Engineering, Malaysia (2008)
Wang, J., Chen, Y., Xie, J., Lin, H.: Model-based Lane Detection and Lane Following for Intelligent Vehicles. IEEE Intelligent Human-Machine Systems and Cybernetics (2010)
Ma, C., Xie, M., Cheng, D.: A Method For Lane Detection Based on Color Clustering. In: 3rd IEEE International Conference on Knowledge Discovery and Data Mining (2010)
Zhu, W., Chen, Q., Wang, H.: Lane Detection in Some Complex Conditions. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, China (2006)
Wang, Y., Shen, D., Teoh, E.K.: Lane Detection Using Spline Model. Pattern Recognition Letter 21, 677–689 (2000)
Tian, M., Fuqiang, L., Wenhong, Z., Chao, X.: Vision Based Lane detection for Active Security in Intelligent Vehicle. In: IEEE Conf. on Vehicular Electronics and Safety, pp. 507–511 (2006)
D’Cruz, C., Zou, J.J.: Lane detection for driver assistance and intelligent vehicule applications. In: International Symposium on Communications and Information Technologies (2007)
Cheng, H., Jeng, B., Tseng, P., Fan, K.: Lane detection with moving vehicle in the traffic scenes. IEEE Trans. on Intelligent Transportation Systems 7, 571–582 (2006)
Gonzalez, J.P., Omit, O.: Lane Detection Using Histogram-Based Segmentation and Decision Trees. In: IEEE Int. Transp. Systems, Conference Proceedings Dearborn (MI), USA (2000)
Zu, K.: Realtime Lane Tracking of Curved Local Road. In: Proceedings of the IEEE Intelligent Transportation Systems Conference Toronto, Canada (2006)
Tsai, M., Hsu-Yung, C., Yu, C., Tseng, C., Fan, K., Hwang, J., Jeng, B.: Lane Detection Using Directional Random Walks. Int. Conf. on Acoustics, Speech, and Signal Processing (2008)
Borkar, A., Hayes, M., Smith, M.T.: Robust Lane Detection and Tracking with Ransac and Kalman filter. In: IEEE International Conference on Image Processing, Egypt (2009)
Tian, M., Liu, F., Hu, Z.: Single Camera 3D Lane Detection and Tracking Based on EKF for Urban Intelligent Vehicle. In: IEEE Int. Conf. on Vehicular Electronics and Safety (2006)
Asif, M., Arshad, M.R., Yousuf, M., Zia, I., Yahya, A.: An Implementation of Active Contour and Kalman Filter for Road Tracking. International Journal of Applied Mathematics (2006)
Wanga, Y., Teoha, E.K., Shenb, D.: Lane detection and tracking using B-Snake. Image and Vision Computing 22, 269–280 (2004)
Boumediene, M., Ouamri, A., Dahnoun, N.: Lane Boundary Detection and Tracking using NNF and HMM Approaches. In: IEEE Intelligent Vehicles Symposium, Turkey (2007)
Ben Romdhane, N., Hammami, M., Ben-Abdallah, H.: An Artificial Vision-based Lane Detection Algorithm. In: Computer Science and its Applications, Jeju, Korea (2009)
Ben Romdhane, N., Hammami, M., Ben-Abdallah, H.: A Comparative Study of Vision-based Lane Detection Methods. In: Advanced Concepts for Intelligent Vision Systems, Belgium (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ben Romdhane, N., Hammami, M., Ben-Abdallah, H. (2011). A Lane Detection and Tracking Method for Driver Assistance System. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23851-2_42
Download citation
DOI: https://doi.org/10.1007/978-3-642-23851-2_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23850-5
Online ISBN: 978-3-642-23851-2
eBook Packages: Computer ScienceComputer Science (R0)