The week's pick
Reseach Article
Real Time Traffic Density Count using Image Processing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 83 - Number 9 |
| Year of Publication: 2013 |
| Authors: Naeem Abbas, Muhammad Tayyab, M. Tahir Qadri |
10.5120/14476-2736
|
Naeem Abbas, Muhammad Tayyab, M. Tahir Qadri . Real Time Traffic Density Count using Image Processing. International Journal of Computer Applications. 83, 9 ( December 2013), 16-19. DOI=10.5120/14476-2736
Abstract
Due to the increase in the number of vehicles day by day, traffic congestions and traffic jams are very common. One method to overcome the traffic problem is to develop an intelligent traffic control system which is based on the measurement of traffic density on the road using real time video and image processing techniques. The theme is to control the traffic by determining the traffic density on each side of the road and control the traffic signal intelligently by using the density information. This paper presents the algorithm to determine the number of vehicles on the road. The density counting algorithm works by comparing the real time frame of live video by the reference image and by searching vehicles only in the region of interest (i. e. , road area). The computed vehicle density can be compared with other direction of the traffic in order to control the traffic signal smartly.
References
- Madhavi Arora, V. K. Banga, "Real Time Traffic Light Control System", 2nd International Conference on Electrical, Electronics and Civil Engineering (ICEECE'2012), pp. 172-176, Singapore, April 28-29, 2012.
- Sabya sanchi kanojia, "Real –time Traffic light control and Congestion avoidance system", International Journal of Engineering Research and Applications (IJERA), pp. 925-929, Vol. 2, Issue 2,Mar-Apr 2012.
- Muhammad Tayyab, "Implementation of Restoration Path Using AODV in VANETs" Master's Dissertation at Brunel University London, UK.
- Anthony J. Venables, "Evaluating Urban Transport Improvements", Journal of Transport Economics and Policy, Vol. 41, No. 2 , pp. 173-188, May, 2007.
- Tommy Gärling, Geertje Schuitema, "Travel Demand Management Targeting Reduced Private Car Use", Journal of Social Issues, Vol. 63, Issue 1, pp. 139–153, March 2007
- Papageorgiou M. , Diakaki C. , Dinopoulou V. , Kotsialos, A. ,"Review of road traffic control strategies", Proceedings of IEEE, Vol. 91, Issue 12, pp. 2043-2067, November 2004.
- Georgios Vigos, Markos Papageorgioua, Yibing Wangb, "Real-time estimation of vehicle-count within signalized links", Journal of Transportation Research Part C: Emerging Technologies, Volume 16, Issue 1, pp. 18–35, February 2008.
- Michael W. Szeto and Denos C. Gazis, "Application of Kalman Filtering to the Surveillance and Control of Traffic Systems", Journal of Transportation Science, vol. 6 pp. . 4419-439 , November 1972.
- Vikramaditya Dangi, Amol Parab, Kshitij Pawar & S. S Rathod, "Image Processing Based Intelligent Traffic Controller", Undergraduate Academic Research Journal (UARJ), Vol. 1, Issue 1, 2012
- Celil Ozkurt and Fatih Camci," Automatic Traffic Density Estimation and Vehicle Classification For Traffic Survillance Systems Using Neural Networks", Journal of Mathematical and Computational Applications, Vol. 14, No. 3, pp. 187-196, 2009.
- Pratishtha Gupta, G. N Purohit, Sweta Pandey, "Traffic Load Computation for Real Time Traffic Signal Control", International Journal of Engineering and Advanced Technology, Vol. 2, Issue 4, April 2013.
- Live Video of CCTV Camera for Traffic Monitoring in Stockholm, available at http://www. trafiken. nu/sv/Stockholm/trafiklaget/Kameror/Roslagsvagen/Albano/
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