Abstract

Traffic management is an increasing problem in both cities and sub urban areas. Authority people involved in traffic management system spend much of time in controlling traffic at junctions. With the advances in technology, monitoring traffic through image processing and video surveillance techniques became the researchers’ attention. These techniques help us in controlling traffic as well as to identification of kamikaze drivers and speed violators. The key focus of this research is to do traffic analysis using video surveillance to detect speedy drivers. A wide range of traffic parameters such as flow of traffic, speed of vehicles and vehicle registration number are the major components involved in this research. In this paper, traffic analysis is carried out based on streaming video data with YOLO tool. In this paper an eco system is developed for object detection, vehicle number detection and the speed of the vehicle using computer vision algorithms. With the application tool developed, traffic control authority people can warn the speedy drivers on the fly.

Highlights

  • Video surveillance acts as a remote eye for traffic authority people

  • Video surveillance grabbed the attention of researchers to articulate image processing with artificial intelligence capabilities using computer vision [19]

  • Automatic License Plate Recognition (ALPR) is a technology used for number plate recognition

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Summary

Introduction

Video surveillance acts as a remote eye for traffic authority people. This includes observing vehicles on roads moving with high speed. In order to reduce accidents, reckless drivers are to be identified. Video surveillance grabbed the attention of researchers to articulate image processing with artificial intelligence capabilities using computer vision [19]. Traffic Control Analysis with Video Surveillance is developed using Image processing techniques in deep learning. Video data is used to analyse the parameters of vehicle like vehicle number, vehicle speed and vehicle categorization. This gives an elaborate way identifying vehicle number, calculating its speed and the type of the vehicle

Related Work
Traffic analysis through Video
Conclusion

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