An Illumination Invariant Change Detection Algorithm
نویسندگان
چکیده
In this paper, a homomorphic filtering based change detection algorithm is proposed to detect moving objects from light-varing monocular image sequences. In our approach, a background model is first constructed, and background subtraction is applied to classify image pixels into background or foreground. We utilize illumination invariant local components to model the background, which are obtained using homomorphic filtering. Threshold for every pixel in the image can be selected automatically to accommodate the change of lighting. In addition, the connectivity information is integrated into the background-foreground classification process by Bayesian estimation. Experimental results show that the presented approach works well in the presence of heavy moving shadows and illumination variance.
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