Publication

Abstract : The traffic problems in the cities across the globe have worsened with the increase in population. Traffic light plays an important role to control the traffic on the road. Hence there is requirement for the better traffic light controlling system. So to improve the traffic light control various techniques have been introduced like fixed timer based systems, using electric and magnetic sensors to detect the vehicle, and neural networks based systems. But all these technique or methods have not given good result due to many problems like difficulty in the installation and maintenance of these equipment’s. So in order to overcome the above problems, researchers introduced vision-based system for collecting and analyzing road traffic data. Image processing technique proved to be the better technique so far because of low cost and low maintenance required. This paper proposes a system which uses canny edge detection technique for identifying the density of the traffic. Simulation results are used to show how canny edge detection technique gives better result compared to other edge detection technique for calculating the traffic parameters.