A novel algorithm is proposed for background estimation using machine learning and statistical pattern recognition. Usually the segmentation of objects in images is achieved by identifying homogeneous regions in individual images or by finding motions of objects in videos. In this paper, we combine the advantages of these approaches for the estimation of background using only two images. The proposed algorithm uses the difference between images to obtain initial estimation of background and then to refine the estimation using machine learning and statistical pattern recognition. Experimental results have shown that the proposed algorithm can achieve promising performance in terms of accuracy and speed.

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