Abstract
This paper describes a low-cost algorithm for tracking lane boundaries in a sequence of images. The algorithm is destined to painted road with slow curvature. The basic idea proposed in our approach is that complete processing of each image can be avoided using the knowledge of the lane markings position in the previous ones. The markings detection is obtained using Radon transform that exploits the markings brilliance relatively to the road surface. The experimental tests proved the robustness of this approach even in shadows presence. The originality of our approach compared to those using the Hough transform is that it does not require any tresholding step and edge detection operator. Consequently, the proposed method is proved to be much faster.
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References
Bertozzi, M., Broggi, A.: GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Transactions on Image Processing 7(1), 62–81 (1998)
Kreucher, C., Lakshmanan, S., Kluge, K.: A Driver Warning System Based on the LOIS Lane Detection Algorithm. In: Proceeding of IEEE International Conference on Intelligent Vehicles, Stuttgart, Germany, pp. 17–22 (1998)
Toft P.: The Radon Transform - Theory and Implementation , Ph.D. thesis, Department of Mathematical Modeling, Technical University of Denmark (June 1996)
Pomerleau, D., Jochem, T.: Rapidly Adapting Machine Vision for Automated vehicle Steering. IEEE expert 11(2), 19–27 (1996)
Chen, M., Jochem, T., Pomerleau, D.: AURORA: A Vision-Based Roadway Departure Warning System. In: Proceeding of IEEE Conference on Intelligent Robots and Systems, vol. 1, pp. 243–248 (1995)
Ran, B., Xianghong Liu, H.: Development of A Vision-based Real Time lane Detection and Tracking System for Intelligent Vehicles. Presented in Transportation Research Board 79th Annual meeting, preprint CD-ROM, Washington DC (2000)
Mc Donald, J.B.: Application of Hough Transform to Lane Detection in Motorway Driving Scenarios. In: Shorten, R., Ward, T., Lysaght, T. (eds.) Proceeding of Irish Signals and Systems Conference, June 25-27 (2001)
Bertozzi, M., Broggi, A., Cellario, M., Fascioli, A., Lombardi, P., Porta, M.: Artificial Vision in Road Vehicles. Proc of the IEEE - Special issue onTechnology and Tools for Visual Perception 90(7), 1258–1271 (2002)
Fung, P., Lee, W., King, I.: Randomized Generalized Hough Transform for 2-D Grayscale Object Detection. In: Proceeding of ICPR 1996, Vienna, Austria, August 25 - 30, pp. 511–515 (1996)
Hansen, K., Andersen, J.D.: Understanding the Hough transform: Hough cell support and its utilization. Image and Vision Computing 15, 205–218 (1977)
Bertozzi, M., Broggi, A., Cellario, M., Fascioli, A., Lombardi, P., Porta, M.: Artificial Vision in Road Vehicles. Proc of the IEEE - Special issue onTechnology and Tools for Visual Perception 90(7), 1258–1271 (2002)
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Nourine, R., Boudihir, M.E., Khelifi, S.F. (2004). Application of Radon Transform to Lane Boundaries Tracking. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_69
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DOI: https://doi.org/10.1007/978-3-540-30126-4_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23240-7
Online ISBN: 978-3-540-30126-4
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