Skip to Main Content
Background subtraction is an essential technique for automatic video analysis. The main idea is to construct and update the model of the background scene. Foreground pixels are detected if they deviate from the background model to a certain extent. The model can consist of color, texture and gradient information . In this paper, we focus on both color and texture information. The proposed texture feature is based on local binary pattern (LBP), while the color feature is represented by local color pattern (LCP). LBP is known to work well on texture rich regions and is invariant to subtle illumination variations, but it is inefficient on uniform regions. In view of this, color information can be incorporated to complement the texture feature. On the other hand, when the scene contrast or video quality is poor, color information may be unreliable and should be assigned lower priority than texture information. We propose a fuzzy rule-based system that adaptively adjusts the weights of the texture and color features based on the pixel's local properties. Experimental results on real scenes demonstrate the robustness of the proposed method.