The week's pick
Reseach Article
An Algorithm for Accurate Taillight Detection at Night
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 100 - Number 12 |
| Year of Publication: 2014 |
| Authors: Noppakun Boonsim, Simant Prakoonwit |
10.5120/17579-8345
|
Noppakun Boonsim, Simant Prakoonwit . An Algorithm for Accurate Taillight Detection at Night. International Journal of Computer Applications. 100, 12 ( August 2014), 31-35. DOI=10.5120/17579-8345
Abstract
Vehicle detection is an important process of many advance driver assistance system (ADAS) such as forward collision avoidance, Time to collision (TTC) and Intelligence headlight control (IHC). This paper presents a new algorithm to detect a vehicle ahead by using taillight pair. First, the proposed method extracts taillight candidate regions by filtering taillight colour regions and applying morphological operations. Second, pairing each candidates and pair symmetry analysis steps are implemented in order to have taillight positions. The aim of this work is to improve the accuracy of taillight detection at night with many bright spot candidates from streetlamps and other factors from complex scenes. Experiments on still images dataset show that the proposed algorithm can improve the taillight detection accuracy rate and robust under limited light images.
References
- Traffic Safety Basic Facts 2007-Motorways. EUR. ROAD SAFETY OBSERVATORY.
- WANG, C. -C. , HUANG, S. -S. , and FU, L. -C. 2005. Driver assistance system for lane detection and vehicle recognition with night vision. In Proc. IEEE/RSJ International Conference on Intelligent Robots and System.
- O'MALLEY, R. , GLAVIN, M. , and JONES, E. 2008 Vehicle detection at night based on taillight detection. In Proc. 1st International Symposium on Vehicular Computing System.
- LI, Y. , and YAO, Q. 2012. Rear lamp based vehicle detection and tracking for complex traffic conditions. In Proc. 9th IEEE International Conference on Networking, Sensing and Control.
- O'MALLEY, R. , JONES, E. , and GLAVIN, M. Rear-lamp vehicle detection and tracking in low-exposure color video for night conditions. IEEE Transactions on Intelligent Transportation Systems. vol. 11, no 2, (June 2010) ,453-462.
- O'MALLEY, R. , GLAVIN, M. , and JONES, E. Vision-based detection and tracking of vehicles to the rear with perspective correction in low-light conditions. IET Transactions on Intelligent Transport Systems. vol. 5, no. 1, (March 2011), 1-10.
- CHAN, Y. -M. , HUANG, S. -S. , FU, L. -C. , and HSIAO, P. -Y. 2007. Vehicle Detection under Various Lighting Conditions by Incorporating Particle Filter. In Proc. IEEE Conference on Intelligent Transportation Systems.
- MING, Q. , and JO, K. –H. 2011. Vehicle detection using tail light segmentation. In Proc. 6th International Forum on Strategic Technology.
- ZHOU, S. , LI, J. , SHEN, Z. , and YING, L. A night time application for a real-time vehicle detection algorithm based on computer vision. Research Journal of Applied Sciences, Engineering and Technology. vol. 5, no. 10, (March 2013), 3037-3043.
- CHEN, Y. L. Nighttime vehicle light detection on a moving vehicle using image segmentation and analysis techniques, WSEAS TRANSACTIONS on COMPUTERS, vol. 3, no. 3, (March 2009), 506-515.
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