Abstract
Lane detection consists of detecting the lane limits where the vehicle carrying the camera is moving. The aim of this study is to propose a lane detection method through digital image processing. Morphological filtering, Hough transform and linear parabolic fitting are applied to realize this task. The results of our proposed method are compared with three proposed researches. The method 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.
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)
Guo, L., Wang, J., Li, K.: Lane Keeping System Based on THASV-II Platform. In: IEEE International Conference on Vehicular Electronics and Safety (2006)
Dariu, M.G., Uwe, F., Wohler, C., Gorzig, S.: Real-time vision for intelligent vehicles. IEEE Instrumentation and Measurement Magazine (2001)
Assidiq, A., Khalifa, O., Islam, R., Khan, S.: Real Time Lane Detection for Autonomous Vehicles. In: Proceedings of the International Conference on Computer and Communication Engineering, Kuala Lumpur, Malaysia (2008)
Yeh, C., Chen, Y.: Development of Vision-Based Lane and Vehicle Detecting Systems via the Implementation with a Dual-Core DSP. In: IEEE Int. Transp. Systems Conference, Canada (2006)
Lin, H., Ko, S., Hi, W., Kim, Y., Kim, H.: Lane departure identification on Highway with searching the region of interest on Hough space. In: International Conference on Control, Automation and Systems, Seoul, Korea (2008)
Jung, C.R., Christian, R.K.: A Robust Linear-Parabolic Model for Lane Following. In: Proceedings of the XVII Brazilian Symposium on Computer Graphics and Image Processing (2004)
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, Beijing, 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 Conference 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: 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. In: International Conference on Acoustics, Speech, and Signal Processing (2008)
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)
Lim, K.H., Seng, K.P., Ngo, A.C., Ang, L.: Real-time Implementation of Vision-based Lane Detection and Tracking. In: Int. Conference on Intelligent Human-Machine Systems and Cybernetics (2009)
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 Istanbul, Turkey (2007)
Ben Romdhane, N., Hammami, M., Ben-Abdallah, H.: An Artificial Vision-based Lane Detection Algorithm. In: International Conference on Computer Science and its Applications, Korea (2009)
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 Comparative Study of Vision-Based Lane Detection Methods. In: Blanc-Talon, J., Kleihorst, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2011. Lecture Notes in Computer Science, vol 6915. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23687-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-23687-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23686-0
Online ISBN: 978-3-642-23687-7
eBook Packages: Computer ScienceComputer Science (R0)