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  A Comparative Analysis of Digital Image Processing Techniques on Real Time Traffic Control Systems  
  Authors : Detty M Panicker; Radhakrishnan B
  Cite as:


Traffic control is considered as one of the fastest developing technologies in the world. In India with the growing number of vehicles, traffic jam at junctions has become a serious issue. Normally Traffic police, Timers, Electronic sensors are used to control the traffic jam. But nowadays, image processing techniques are used to control traffic. This paper discuss about the various traffic control techniques and their comparisons. In order to reduce the traffic problems real time traffic control system using image processing is very advantageous.


Published In : IJCSN Journal Volume 5, Issue 1

Date of Publication : February 2016

Pages : 115-120

Figures :01

Tables : 01

Publication Link : A Comparative Analysis of Digital Image Processing Techniques on Real Time Traffic Control Systems




Detty M Panicker : received her B.Tech (Computer Science & Engineering) degree from University of Kerala, Trivandrum in 2014. She is currently pursuing her Masters in Computer Science & Engineering from University of Kerala. Her research interests focuses on image processing, data mining, and image mining.

Radhakrishnan B : is working as Asst. Professor in computer science department. He has more than 14 years experience in teaching and has published papers on data mining and image processing. His research interests include image processing, data mining, image mining.








Traffic light

Image Processing

Image Matching

Edge Detection

Background Subtraction

In this paper we discussed about the existing traffic control system and their drawback. To overcome from those drawbacks we can build a flexible traffic light control system based on traffic density. To find the traffic density edge detection techniques can be used. Gaussian based edge detection is sensitive to noise. The canny edge detection gives best performance even in noise condition compare to other first order edge detection and more costly as compared to Sobel, Prewitt and Robert’s operator. Improve the performance of background subtraction, Traffic Queue Detection Algorithm, segmentation, morphological operation etc. A best edge detection algorithm is necessary to provide an errorless solution or fuzzy logic, morphological based edge detection technique for regulating traffic light system based on traffic density to save the time and to reduce operating cost.










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