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A Video Traffic Flow Detection System Based on Machine Vision

  • Wang, Xin-Xin (School of Computer and Information Engineering, Luoyang Institute of Science and Technology) ;
  • Zhao, Xiao-Ming (School of Electrical and Automation, Luoyang Institute of Science and Technology) ;
  • Shen, Yu (School of Electronic and Information Engineering, Lanzhou Jiaotong University)
  • Received : 2017.10.11
  • Accepted : 2019.04.22
  • Published : 2019.10.31

Abstract

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

Keywords

Background Difference Method;Intelligent Traffic System;Motion Object Location;Object Detection;Vehicle Location

Acknowledgement

Supported by : National Natural Science Foundation of China

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