Robust Change Detection by Fusing Intensity and Texture Differences

Abstract

The paper proposes a novel technique for robust change detection based upon the integration of intensity and texture differences between two frames. A new texture difference measure based on the relations between gradient vectors is described. The robustness of the measure with respect to noise and illumination changes has been analyzed. Two ways to integrate the intensity and texture differences are proposed. The first combines two measures according to the weightage of texture evidence, while the second takes into additional constraint of smoothness. The parameters of the algorithm are selected automatically. The computational complexity analysis indicates that the proposed technique can run in real-time. Experimental results show that by exploiting both intensity and texture differences for change detection, one can obtain much better segmentation results than using the intensity or structure difference alone.