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Real Time Traffic Density Count using Image Processing

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Alisha Janrao, Mudit Gupta, Divya Chandwani, U. A. Joglekar

Alisha Janrao, Mudit Gupta, Divya Chandwani and U A Joglekar. Real Time Traffic Density Count using Image Processing. International Journal of Computer Applications 162(10):8-12, March 2017. BibTeX

	author = {Alisha Janrao and Mudit Gupta and Divya Chandwani and U. A. Joglekar},
	title = {Real Time Traffic Density Count using Image Processing},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {162},
	number = {10},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {8-12},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017913334},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Nowadays traffic jams and congestion is a common issue because of the day by day increment of numerous vehicles. A smart traffic control system can be one of the solutions to the above problem. This can be done by measuring the vehicular density on that road wherein real time image and video processing techniques will be used. The main aim is to coordinate the traffic by keeping a check of its density from all the sides and thereby controlling the traffic signal intelligently. This paper will present an algorithm so as to determine the amount of vehicles on that road. This density counting algorithm will work by the comparison between one frame of the live video (real time) and the reference image followed by looking for the vehicles in the desired region. The 0traffic signal will be controlled smartly by comparing the vehicle density and the direction of the traffic.


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Traffic Density count, Image Processing, Intelligent Controlling of Traffic, Camera, Raspberry Pi, Server.