Efficient Moving Vehicle Detection Algorithm for Various Traffic Conditions
Sridevi N1, M Meenakshi2

1Sridevi N, Department of EIE, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India.
2M Meenakshi, Department of EIE, Dr. Ambedkar Institute of Technology, Bangalore, Karnataka, India.

Manuscript received on 03 August 2019. | Revised Manuscript received on 09 August 2019. | Manuscript published on 30 September 2019. | PP: 6069-6076 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5619098319/2019©BEIESP | DOI: 10.35940/ijrte.C5619.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Many computer vision applications needs to detect moving object from an input video sequences. The main applications of this are traffic monitoring, visual surveillance, people tracking and security etc. Among these, traffic monitoring is one of the most difficult tasks in real time video processing. Many algorithms are introduced to monitor traffic accurately. But most of the cases, the detection accuracy is very less and the detection time is higher which makes the algorithms are not suitable for real time applications. In this paper, a new technique to detect moving vehicle efficiently using Modified Gaussian Mixture Model and Modified Blob Detection techniques is proposed. The modified Gaussian Mixture model generates the background from overall probability of the complete data set and by calculating the required step size from the frame differences. The modified Blob Analysis is then used to classify proper moving objects. The simulation results shows that the method accurately detect the target.
Keywords: Vehicle Detection, Gaussian Mixture Model, Morphological Filter, Blob Detection Techniques etc.

Scope of the Article:
Energy Efficient Building Technology