DIP BASED TRAFFIC SIGNAL CONTROLLING SYSTEM

Abstract

One important application of image processing and computer vision is traffic monitoring and control. This report presents a system for detection of moving vehicles approaching an intersection from color images acquired by a stationary camera in the context of traffic light control systems. Traffic engineers require various types of road traffic data to manage the traffic. The current sensors (inductive loops and axle sensors etc.) cannot collect all the data that are of interest to traffic engineers. Most important of all, if the data is to be collected at a different location, the installation of these equipments, which needs to be buried beneath the road, creates serious traffic disturbances. In order to overcome the above problems, many researchers have used vision-based system for collecting and analyzing road traffic data. In this project we use morphological edge detection techniques to detect vehicles. Once the vehicles have been detected, this information is used for calculating various traffic parameters. This method has been implemented on a Pentium-based microcomputer. We also have compared our system with traditional image processing based systems and the results indicate that our proposed system provides better results than the traditional image processing based systems.