Abstract
Traffic is the serious issue which each nation faces due to the expansion in number of vehicles. One of the strategies to beat the traffic issue is to build up a smart traffic control framework which depends on computing the traffic density and about utilizing constant video and picture preparing procedures. The topic is to control the traffic by deciding the traffic density on each roadside and control the traffic signal smartly by utilizing the density data. In this paper, an automated system based on processing of real time videos is proposed for detection of vehicles and recording count of them. The System will consist of various stages which includes Object Car Detection and Signal variation based on density. Captured video will be converted into frames and which will be pre-processed for object detection using Haar-Cascade than detected object count will be used to obtain the density and manipulate the signal accordingly. The density count algorithm works by contrasting the ongoing edge of live video by the reference picture and via looking through vehicles just in the district of intrigue (for example street region). The figured vehicle thickness can be contrasted and other course of the traffic so as to perform control of the traffic flags in more smart and proficient manner.
Highlights
Review of literatureThe proposed system is aimed to give a comprehensive application to dynamically manage the traffic light systems depends on the current vehicle count
Traffic clogging has become a difficult issue in urban areas
The fundamental explanation is the increase in population in the urban area that along these lines there is high vehicular travel, which births clog issue
Summary
The proposed system is aimed to give a comprehensive application to dynamically manage the traffic light systems depends on the current vehicle count. Gaussian probabilistic model is used for classification of vehicles, Kalman filter is used to detect the vehicles at the junction of the traffic light timer will be adjusted according This proposed system will improve the traffic management system significantly by calculating accurate vehicle density on the roads. This paper estimates the number of vehicles present, and the density is determined ac- cording to the total This is intended to develop a system that uses camera to perform execution based on vehicle density, i.e. vehicle counting. It proves that video processing is a better option for calculating traffic density using OpenCV. The traffic signal manipulation is successfully achieved through the count of the vehicles detected by the proposed system and reduces the traffic congestion at the intersections [3] [9]
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