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Reseach Article

Lane Detection Techniques: A Review

by Gurveen Kaur, Dinesh Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 10
Year of Publication: 2015
Authors: Gurveen Kaur, Dinesh Kumar
10.5120/19700-0923

Gurveen Kaur, Dinesh Kumar . Lane Detection Techniques: A Review. International Journal of Computer Applications. 112, 10 ( February 2015), 4-8. DOI=10.5120/19700-0923

@article{ 10.5120/19700-0923,
author = { Gurveen Kaur, Dinesh Kumar },
title = { Lane Detection Techniques: A Review },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 10 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 4-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number10/19700-0923/ },
doi = { 10.5120/19700-0923 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:04.846767+05:30
%A Gurveen Kaur
%A Dinesh Kumar
%T Lane Detection Techniques: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 10
%P 4-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many people die each year in roadway departure crashes caused by driver inattention. Lane detection systems are useful in avoiding these accidents as safety is the main purpose of these systems. Such systems have the goal to detect the lane marks and to warn the driver in case the vehicle has a tendency to depart from the lane. A lane detection system is an important element of many intelligent transport systems. Lane detection is a challenging task because of the varying road conditions that one can come across while driving. In the past few years, numerous approaches for lane detection were proposed and successfully demonstrated. In this paper, a comprehensive review of the literature in lane detection techniques is presented. The main objective of this paper is to discover the limitations of the existing lane detection methods.

References
  1. F. Mariut, C. Fosalau and D. Petrisor, "Lane Mark Detection Using Hough Transform", In IEEE International Conference and Exposition on Electrical and Power Engineering, pp. 871 - 875, 2012.
  2. S. Srivastava, R. Singal and M. Lumb, " Efficient Lane Detection Algorithm using Different Filtering Techniques", International Journal of Computer Applications, vol. 88, no. 3, pp. 975-8887, 2014.
  3. A. Borkar, M. Hayes, M. T. Smith and S. Pankanti , "A Layered Approach To Robust Lane Detection At Night" , In IEEE International Conference and Exposition on Electrical and Power Engineering, Iasi, Romania, pp. 735 - 739, 2011.
  4. K. Ghazali, R. Xiao and J. Ma, "Road Lane Detection Using H-Maxima and Improved Hough Transform", Fourth International Conference on Computational Intelligence, Modelling and Simulation, pp: 2166-8531, 2011.
  5. Z. Kim, "Robust Lane Detection and Tracking in Challenging Scenarios", In IEEE Transactions on Intelligent Transportation Systems, vol. 9, no. 1, pp. 16 - 26, 2008.
  6. M. Aly, "Real time Detection of Lane Markers in Urban Streets", In IEEE Intelligent Vehicles Symposium, pp. 7 - 12, 2008.
  7. J. C. McCall and M. M. Trivedi, "Video-based Lane Estimation and Tracking for Driver Assistance: Survey, System, and Evaluation", IEEE Transactions on Intelligent Transportation Systems, vol. 7, pp. 20-37, 2006.
  8. Y. Wang, E. K. Teoh and D. Shen, "Lane Detection and Tracking Using B-snake," Image and Vision Computing, vol. 22, pp. 269-280, 2004.
  9. A. Broggi and S. Berte, "Vision-based Road Detection in Automotive Systems: a Real-time Expectation-driven Approach", Journal of Artificial Intelligence Research, vol. 3, pp. 325-348, 1995.
  10. M. Bertozzi and A. Broggi, "GOLD: A Parallel Real-time Stereo Vision System for Generic Obstacle and Lane Detection", IEEE Transactions of Image Processing, pp. 62-81, 1998.
  11. S. G. Jeong, C. S. Kim, K. S. Yoon, J. N. Lee, J. I. Bae, and M. H. Lee, "Real-time Lane Detection for Autonomous Navigation",IEEE Proc. Intelligent Transportation Systems, pp. 508–513, 2001.
  12. Y. Wang, E. K. Teoh and D. Shen, "Improved Lane Detection and Tracking Using B-snake," Image and Vision Computing, vol. 20, pp. 259-272, 2005.
  13. C. R. Jung and C. R. Kelber, "A Lane Departure Warning System Using Lateral Offset with Uncalibrated Camera," Proc. IEEE Conf. on Intelligent Transportation Systems, pp. 102-107, 2005.
  14. D. J. Kang, J. W. Choi and I. S. Kweon, "Finding and Tracking Road Lanes Using Line-snakes", Proceedings of Conference on Intelligent Vehicle, pp. 189-194, 1996.
  15. Z. Kim, "Real-time lane tracking of curved local road", Proc. IEEE Conf. on Intelligent Transportation System, pp. 1149-1155, 2006.
  16. Y. Wang, D. Shen and E. K. Teoh, "Lane Detection Using Spline Model", Pattern Recognition Letters vol. 21, pp. 677-689, 2000.
  17. Q. Lin, Y. Han and H. Hahn, "Real-time lane departure detection based on extended edge-linking algorithm", In IEEE 2nd International Conference on Computer Research and Development, pp. 725-730, 2010.
  18. O. O. Khalifa and A. H. A Hashim, "Vision-Based Lane Detection for Autonomous Artificial Intelligent Vehicles", In IEEE International Conference on Semantic Computing, pp. 636 - 641, 2009.
  19. K. Ghazali, R. Xiao and J. Ma, "Road Lane Detection Using H-Maxima and Improved Hough Transform", Fourth International Conference on Computational Intelligence, Modelling and Simulation, pp: 2166-8531, 2012.
  20. T. T Tran, C. S Bae, Y. N. Kim, H. M. Cho, and S. B. Cho, "An Adaptive Method for Lane Marking Detection Based on HSI Color Model", ICIC, CCIS 93, pp. 304–311, 2010.
  21. D. Pomerleau and Jochem, "Rapidly Adapting Machine Vision for Automated Vehicle Steering, IEEE, 1996.
  22. B. M, Broggi, "GOLD: A parallel real-time stereo Vision system for generic obstacle and lane detection", IEEE Transactions on Image Processing, pp. 4-6, 1998.
  23. C. Kreucher and S. K. Lakshmanan, A Driver warning System based on the LOIS Lane detection Algorithm, Proceeding of IEEE International Conference On Intelligent Vehicles. pp. 17 -22, 1998.
  24. Y. Wang, E. K. Teoha, D. Shen. Lane detection and tracking using B-Snake", In: Image and Vision Computing 22, pp: 269-28, 2004.
  25. M. Chen. , T. Jochem and D. T. Pomerleau, "AURORA: A Vision-Based Roadway Departure Warning System", In Proceeding of IEEE Conference on Intelligent Robots and Systems, 2004.
  26. C. R. Jung and C. R. Kelber, "Lane following and lane departure using a linear-parabolic model" In: Image and Vision Computing, pp. 1192–1202, 2005.
  27. M. Meuter, S. Muller, A. Mika, S. Hold, C. Nunn and A. Kummert, "A Novel Approach to Lane Detection and Tracking", In IEEE 12th International Conference on Intelligent Transportation Systems, pp. 1-6, 2009.
  28. S. Zhou, Y. Ziang, J. Xi, J. Gong, G. Xiong and H. Chen, "A novel lane detection based on geometrical model and gabor filter", in IEEE Intelligent Vehicles Symposium, pp. 59-64, 2010.
  29. Z. Teng, J. H. Kin and D. J. Kang, "Real-time Lane detection by using multiple cues", In IEEE International Conference on Control Automation and Systems, , pp. 2334 - 2337, 2010.
  30. N. Phaneendra, G. Goud and V. Padmaja, "Accident Avoiding System Using Lane Detection", International Journal of Research in Electronics and Communication Engineering, vol. 1, no. 1, pp. 1 - 4, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Lane detection Lane Colorization.