A novel algorithm to segment foreground from a similarly colored background

Color similarity between the background and the foreground causes most moving object detection algorithms to fail. This paper proposes a novel algorithm designed to segment the foreground from a similarly colored background. Central to this algorithm is that the motion cue of the moving object is useful for foreground modeling. We predict the position of the moving object in the current frame using historical motion information, and then use the prediction information to construct a predictive model. The mixture foreground model is a union of the predictive model and the general foreground model. Final segmentation is obtained by combining a likelihood modification technique and the mixture foreground model. Experimental results on typical sequences show that the proposed algorithm is efficient.