An Overview on Vehicle Detection and Classification System by Gaussian Mixture Models

Authors

  • S. Rakesh  Assistant Professor, Department of Information Technology, Chaitanya Bharathi Institute of Technology, India
  • Dr. Nagaratna P Hegde  Professor, Department of CSE, Vasavi College of Engineering, India

Keywords:

Gaussian Mixture Models, Vehicle Detection, Classification System

Abstract

An efficient traffic control system by detecting as well as adding up the vehicle numbers several times and areas are required. Traffic estimate from the fixed graphics is the vital problem for automating traffic control commands. Today's traffic monitoring system possesses no significance on the online traffic situation, which results in unskilled traffic management units. These traffic cooking timers just reveal the pre-set time, this feels like utilizing an available loop system. If our company settle a sealed loop system making use of cam, it is achievable to forecast the needed opportunity on traffic light timers according to the traffic thickness. If the traffic signal timers are presenting simply required opportunity to manage the traffic, after that the time wasted on unwanted environment-friendly indicators (eco-friendly sign, when there is no traffic) will be saved. This paper provides an overview on vehicle detection and classification system by gaussian mixture models.

References

  1. Bilal Ghazal, Khaled ElKhatib “Smart Traffic Light Control System”. Conference Paper- April 2016.
  2. Dinesh Rotake, Prof. Swapnil Karmore “Intelligent Traffic Signal Control System Using Embedded System”. G.H Raisoni College of Engineering, Nagpur. Innovative Systems Design and Engineering, 2012.
  3. Malik Tubaishatr, Ti Shang and Hongchi Shi “Adaptive Traffic Light Control with Wireless Sensor Networks”. Article January 2007.
  4. Nang Hom Kham, Chaw Myat New “Implementation of Modern Traffic Light Control System”. Department of Electronic Engineering, Mandalay Technological University, Myanmar. International Journal of Scientific and Research Publications, June 2014.
  5. Khalil M. Yousef, Jamal N. Al-Karaki, Ali M. Shatnawi “Intelligent Traffic Light Flow Control System Using Wireless Sensors Networks”.Journal of Information Science and Engineering, May 2010
  6. Shilpa S. Chavan, Dr. R. S. Deshpande & J. G. Rana (2009) “Design of Intelligent Traffic Light Controller Using Embedded System” Second International Conference on Emerging Trends in Engineering and Technology
  7. Reynolds, D.A.: A Gaussian Mixture Modeling Approach to Text-Independent Speaker Identification. PhD thesis, Georgia Institute of Technology (1992)
  8. Reynolds, D.A., Rose, R.C.: Robust Text-Independent Speaker Identification using Gaussian Mixture Speaker Models. IEEE Transac- tions on Acoustics, Speech, and Signal Processing 3(1) (1995) 72–83
  9. Dempster, A., Laird, N., Rubin, D.: Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society 39(1) (1977) 1–38

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Published

2020-05-30

Issue

Section

Research Articles

How to Cite

[1]
S. Rakesh, Dr. Nagaratna P Hegde, " An Overview on Vehicle Detection and Classification System by Gaussian Mixture Models, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 7, Issue 3, pp.485-491, May-June-2020.