Abstract
The authors, Cosmin Rus, Răzvan Marcuş and Olimpiu Stoicuța, regret that this article is an accidental duplication of an article that has already been published: https://www.mathworks.com/matlabcentral/fileexchange/52456-analyzing-trafficusing-a-webcam-a-raspberry-pi-and-thingspeak. The duplicate article has therefore been withdrawn. The Guest Editors have given their approval for this decision.
Highlights
The result of the increase in vehicle traffic has caused many problems
The density of vehicles circulating on a particular road is determined in real time
The results of the proposed method with regard to the accuracy and time required are better compared to other methods
Summary
The result of the increase in vehicle traffic has caused many problems. For example, traffic e accidents, traffic congestion, air pollution caused by traffic and so on. R Intelligent Transport System (ITS), which can use traffic flow data based on traffic monitoring at traffic junctions for congestion detection. In order to process the information and to monitor the results, in order to better understand the flow of traffic, an increasing dependence on traffic surveillance requires better detection of vehicles in an extended area. Automated detection of vehicles in video surveillance data is a topical and extremely important issue for computers with important practical applications such as traffic analysis and security. Automated detection and tracking of video surveillance data is a very difficult issue in computer vision with important practical applications such as traffic analysis and security. Video surveillance systems focus on background d modeling, vehicle classification and tracking. It is necessary in some locations to create an infrastructure suitable for the entire system in terms of power supply from one source of energy as well as to create possibilities for the effective fixation of the entire system in order to allow the data to be safely recorded
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