Background Subtraction Techniques for Moving Object Detection in Video Frames
Vrunda A. Mahamuni1, Madhuri Khambete2
1Vrunda A. Mahamuni, Department of Electronics and Telecommunication, Cummins College of Engineering for Women, Pune, India.
2Dr. Madhuri Khambete, Principal, Cummins College of Engineering for Women, Pune, India.
Manuscript received on September 22, 2013. | Revised Manuscript received on October 15, 2013. | Manuscript published on October 30, 2013. | PP: 96-98 | Volume-3, Issue-1, October 2013. | Retrieval Number: A2161103113/2013©BEIESP
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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: Identifying moving objects is a critical task for many computer vision applications. Background subtraction approach is used to separate the moving objects from the background. Many different methods have been proposed over the recent years. This paper provides implementation of five background subtraction techniques these are , Frame differencing, Mean, Median, Single Gaussian distribution and codebook. Implemented techniques are compared based on different parameters e.g. TP rate FP rate Precision and computation time, Such a comparison can effectively guide the designer to select the most suitable technique for a given application in a principled way.
Keywords: Background modeling, BGS, BG, Foreground.