An Advanced Motion Detection Algorithm with Video Quality Analysis for Video Surveillance Systems

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Shivendra Yadav
Prof. Rahul Dubey, Prof. M.Ahmed


Motion detection is the first important process in the mining of information concerning moving objects and makes use of stabilization in efficient areas, such as tracking, organization, identification, and so on. In this paper, we propose a new and perfect approach to motion detection for the automatic video surveillance system. Our method achieves total detection of moving objects by concerning three significant proposed modules: a background modeling (BM) module, block based module, and a human detection module. In the proposed work our method of quality detection uses wavelet threshold algorithms. The analyses show that our proposed method has a considerably higher scale of efficiency, outperforming other methods by a confusion matrix accuracy rate of up to 65%.

Keywords: Motion Detection, Background Modeling (BM), Block Based, Human Detection, Wavelet Threshold Algorithm, Confusion Matrix


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