Vehicle Tracking System and Speed Estimation Utilizing Optimal Technique

One of the most active study fields in the computer vision community is using video in traffic monitoring. The system Traffic Monitor in which uses a hybrid technique for autonomous vehicle monitoring and classification on highways utilizing a basic stationary calibrated camera. This paper discusses the vehicle global positioning framework system, which allows us to estimate the vehicle’s speed. Optical stream is the technology used for speed testing. The optical stream is used to distinguish between the article’s undeniable development in the edges and the scenes. Optical stream is the relationship between the clear developments of the objects in the scene’s housings. It covers the pace of the video’s more brilliant concealing pixels. Convolution Neural Network (CNN) is one of the various solutions for the readiness model because such unending systems are employed. Housings are removed from the video that is utilized to test the model’s readiness. The final results are acceptable and can aid in the development of a continuous system that can track and monitor the speed of vehicles as they go throughout town.