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Background Subtraction Algorithm for Moving Object Detection Using SAMEER-TU Dataset

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 335)


Identifying moving objects plays an important role in video-based applications. In this paper, a background subtraction approach for object detection technique is proposed, which is an improvised version of an existing background subtraction algorithm called visual background extractor (ViBe). Here, the performance of the existing technique has been modified by a median filter. This technique is implemented on different existing databases and also on newly created Society of Applied Microwave Electronics Engineering and Research-Tripura University (SAMEER-TU) dataset. The detection accuracy of the technique is also measured, and a comparison is also carried out between existing and proposed technique, and results are reported in experimental results, in terms of detection accuracy for color video sequence.


  • ViBe
  • Background subtraction

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First author is thankful to the Society for Applied Microwave Electronics Engineering and Research (SAMEER), R&D Lab of Department of Electronics and Information Technology (DeitY), Ministry of Communications and Information Technology, Government of India. The database is presented here is being created in the Biometrics Laboratory of Computer Science Engineering Department of Tripura University (A Central University), India under the project entitled “Development of Thermography Infrastructure facility for Security and Navigation System-Phase-1”, grant no SMR/PD(R)/NER/2012–13/Thermography, Dated: 22nd March 2013 from the Society for Applied Microwave Electronics Engineering and Research (SAMEER), IIT Bombay Campus, Powai, Mumbai 400076.

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Correspondence to Kakali Das .

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Das, K., Bhowmik, M.K., De, B.K., Bhattacharjee, D. (2015). Background Subtraction Algorithm for Moving Object Detection Using SAMEER-TU Dataset. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 335. Springer, New Delhi.

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  • Print ISBN: 978-81-322-2216-3

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