ABSTRACT
Real-time traffic management is a big problem in metro cities or big cities. Traffic problem increases day to day in daily life. Due to this, a real-time traffic analyzer is required, which predicts the traffic density or traffic roadblock information. The type of technology and method help us in public place road jam avoidance. There are different methods presented by researchers, which are based on image-based traffic measurement. But the current era requirement is run-time traffic intensity measurement that provides absolutes values of traffic at frame/sound. In this presented work, we try to give the proper solution to this problem with the help of video processing. The book chapter first shows a survey on various traffic detection schemes presented in the last era. Researchers have used several techniques such as image processing, morphological operations, and edge detection techniques for traffic management. The proposed traffic detection and management are based totally on the horizontal as well as vertical facet detection video frames. After that, apply morphological operation accurate vehicle detection. Finally, plot the traffic density and also indicate the level of traffic. In the proposed work divide the three different levels of traffic intensities that are high, low and medium. The bar graph shows three levels of traffic. In several traffic videos, the suggested approach outperforms others in terms of accuracy as well as traffic management.
