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An Effective Method of Head Lamp and Tail Lamp Recognition for Night Time Vehicle Detection

Authors: Ho-Youl Jung, Hyun-Koo Kim, Sagong Kuk, MinKwan Kim


This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, to effectively extract spotlight of interest, a segmentation process based on automatic multi-level threshold method is applied on the road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process based on light tracking and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with near infrared mono-camera and tested it in the urban and rural roads. Through the test, classification performances are above 97% of true positive rate evaluated on real-time environment. Our method also has good performance in the case of clear, fog and rain weather.

Keywords: Assistance Driving System, Multi-level Threshold Method, Near Infrared Mono Camera, Nighttime Vehicle Detection

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[1] Yukio Akashi and Mark Rea, "The effect of oncoming headlight glare on peripheral detection under a mesopic light level", Progress In Automotive Lighting, 2001.
[2] Yen-Lin Chen, Yuan-Hsin Chen, Chao-Jung Chen, and Bing-Fei Wu, "Nighttime vehicle detection for driver assistance and autonomous vehicles", International Conference on Pattern Recognition, 2006.
[3] M. Sezgin and B. Sankur (2003). "Survey over image thresholding techniques and quantitative performance evaluation", Journal of Electronic Imaging, 2003, vol. 13 no. 1, pp. 146-165.
[4] Nobuyuki Otsu, "A threshold selection method from gray-level histograms", IEEE Trans. Sys., Man., Cyber. 1979, vol. 9, pp. 62-66.
[5] Ping-Sung Liao and Tse-Sheng Chen and Pau-Choo Chung, "A Fast Algorithm for Multilevel Thresholding", J. Inf. Sci. Eng, 2001, vol. 17 no. 5, pp. 713-727.
[6] Mac Queen, J. B. (1967). "Some Methods for classification and Analysis of Multivariate Observations", Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. 1. University of California Press. pp. 281-297.
[7] Horn, Robot Vision, MIT Press, 1996, pp. 69-71
[8] Rauch, H.E.; Tung, F.; Striebel, C.T., "Maximum likelihood estimates of linear dynamic systems", AIAA J Vol. 3, no. 8, 1965, pp. 1445-1450.
[9] David Meyer, Friedrich Leisch, and Kurt Hornik, "The support vector machine under test", Neurocomputing vol. 55, no. 1-2, 2003, pp. 169-186.
[10] Hyun-Koo Kim, Yeonghwan Ju, Jonghun Lee, Yongwan Park, Ho-Youl Jung, "Lane Detection for Adaptive Control of Autonomous Vehicle", Candidate journal for Accreditation, Journal of IEMEK, Vol 4, No 4, pp. 180-188, 2009.