Hybrid Approach for Moving Object Detection in Video Surveillance System

  • PL.D. Lavanya Alagappa University
  • Dr.K. Mahesh lagappa University
Keywords: Video surveillance, YCbCr,, Background subtraction, Frame Differencing, Wiener Filter, Object detection

Abstract

Object tracking detection plays a vital role in video
surveillance system. It is mainly focused in banks, tele
conferencing, shopping and traffic monitor system. Object
tracking is the process of detecting objects which is moving in
sequences frames of a video, to detect the moving objects,
different techniques are used such as background subtraction,
optical flow, GMM(Gaussian Mixture Model). The main
objective of the proposed work is to detect the moving objects
with less complexity and accuracy using frame differencing
method. First background subtraction is detected using recursive
technique. Then noises are removed by wiener filter and YCbCr
Color space for foreground object. In order to obtain accurate
detection, shape based image retrieval technique is used. Finally
the experimental results show that this method can reduce
complexity and generate accurate image without any noises.

Downloads

Download data is not yet available.

Author Biographies

PL.D. Lavanya, Alagappa University

Research Scholar Department of Computer Science and Engineering, Alagappa University,Karaikudi-600 003, Tamilnadu, India

Dr.K. Mahesh, lagappa University

Professor Department of Computer Science and Engineering, Alagappa University,Karaikudi-600 003, Tamilnadu, India.


Published
2016-07-31
How to Cite
Lavanya, P., & Mahesh, D. (2016). Hybrid Approach for Moving Object Detection in Video Surveillance System. IJRDO -Journal of Computer Science Engineering, 2(7), 33-35. https://doi.org/10.53555/cse.v2i7.770