A neural vision based approach for intelligent transportation system

There is a growing demand for road traffic data of all kinds. These data are required by local and central governments for traffic surveillance, control and management. Vehicle detection and monitoring through video image processing is now considered as an attractive and flexible technique. Previous methods proposed by researchers for detecting and monitoring road vehicles are based on traditional image processing algorithms. The method proposed here is based on the combination of edge detection and neural network algorithms. The edge detection technique is used to detect vehicles while neural network is used to monitor vehicle movements. The neural network is trained for various road traffic conditions and is able to provide better results than the traditional image processing algorithms. The results show that the proposed vision approach can detect and monitor vehicles in real-time.