Abstract

One component of smart city is smart transportation, known as Intelligent Transportation Systems (ITS). In this study, we discuss the estimation of moving vehicle speed based on video processing using the Euclidean Distance method. In this study, we examine the effect of camera angles on the video acquisition to speed estimation accuracy. In addition, Region of Interest (ROI) will be designed into three parts to determine which area is the most appropriate to be chosen, so that the estimated vehicle speed will be better. These approaches have never been studied by previous researchers. The separation between the background and foreground is conducted using Gaussian Mixture Models method. By comparing the displacement distance and the number of frames per second (fps), we obtain speed estimate for each vehicle. According to the experimental results, our system can estimate the speed of the vehicle with an accuracy of 99.38%.

Original languageEnglish
Pages (from-to)431-442
Number of pages12
JournalInternational Journal of Computing
Volume18
Issue number4
Publication statusPublished - 2019

Keywords

  • Euclidean distance
  • Gaussian mixture model
  • Region of interest
  • Smart city
  • Vehicle speed estimation

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