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Realtime Robust Curved Lane Detection Algorithm using Gaussian Mixture Model
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 Title & Authors
Realtime Robust Curved Lane Detection Algorithm using Gaussian Mixture Model
Jang, Chanhee; Lee, Sunju; Choi, Changbeom; Kim, Young-Keun;
ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.
curve lane detection;lane departure warning;advanced driver assistance systems;
 Cited by
수색 구조 로봇을 위한 적외선 영상 기반 인명 인식,박정길;이근재;박재병;

제어로봇시스템학회논문지, 2016. vol.22. 4, pp.288-292 crossref(new window)
Lane Detection for Parking Violation Assessments, The International Journal of Fuzzy Logic and Intelligent Systems, 2016, 16, 1, 13  crossref(new windwow)
Y. C. Jang, T. J. Kim, E. Y. Lee, S. C. Jang, H. E. Cho, K. Y. Yoo, T. Y. Choi, Y. H. Kim, D. K. Hwang, S. E. Park, and M. H. Park, "Car accident statistic analysis 2014," Road Traffic Authority of Korea, Korea, Report, 2014.

Y. Wang, E. K. Teoh, and D. Shen, "Lane detection and tracking using B-snake," Image and Vision Computing, vol. 22, pp. 269-280, Apr. 2004. crossref(new window)

B. S. Kim and W. Y. Kim, "Robust lane detection method in varying road condition," Journal of the Institute of Electronics and Information Engineers, vol. 49, no. 1, pp. 88-93, Jan. 2012.

N. Apostoloff and A. Zelinsky, "Robust vision based lane tracking using multiple cues and particle filtering," IEEE Intelligent Vehicles Symposium, 2003. Proceedings, pp. 558-563, Jun. 2003.

H. J. Jang, S. H. Baek, and S. Y. Park, "Model-based curved lane detection using geometric relation between camera and road plane," Journal of Institute of Control, Robotics, and Systems (in Korean), vol. 21, no. 2, pp. 130-136, 2015.

S. J. Han, Y. J. Han, and H. S. Hahn, "Lane and curvature detection algorithm based on the curve template matching method using top view image," Journal of The Institute of Electronics and Information Engineers, vol 47, no. 6, pp. 97-106, Nov. 2010.

M. Aly, "Real time detection of lane Markers in urban streets," Proc. of the IEEE Symposium on Intelligent Vehicles, pp. 7-12, Eindhoven, Netherlands, Jun. 2008.

B. Alberto, "Robust real-time lane and road detection in critical shadow conditions," IEEE International Symposium on Computer Vision, 1995.

M. N. Doncel, "Detection and tracking of vanishing points in dynamic environments," Ph. D. Dissertation, Technical University of Madrid, Madrid, Spain, 2010.

H. Lee and F. Nashashibi, "Lane detection (Part I): mono-vision based method," Project-Team IMARA, INRIA, Ver. 1, Jan. 2013.

Y. J. Lee, J. H. Yang, and N. J. Kwak, "A Lane change recognition system for smart cars," Journal of Institute of Control, Robotics, and Systems (in Korean), vol. 21, no. 1, pp. 46-51, 2015.

M. A. Fischler and R. C. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM, vol. 24, no. 6, pp. 381-395, Jun. 1981. crossref(new window)

J. A. Bilmes, "A gentle tutorial of the em algorithm and its applications to parameter estimation for gaussian mixture and hidden markov models," International Computer Science Institute, Apr. 1998.