A new combination method for background subtraction in video sequences

Identifying moving objects from a video sequence is a fundamental and critical talk in many computer-vision application. It is an Important part of visual tracking system. In this paper, a new algorithm for background subtraction has been proposed and its performance wat investigated and compared. It is a combination of three background subtraction algorithms; frame difference, approximated median, and Mixture of Ganssian. Each algorithm first they are modified and then a decision level fusion algorithm applied to the result. The performance of these algorithms are compared before and after combinations. It has been found that the percentage error for the pixel in each frame has reduced remarkably when applying the combinational algorithm.