Background models are used for object detection in many computer vision algorithms.In this article, we propose a novel background modeling method basedon frequency for spatially varying and time repetitive textured background.The local Fourier Transform is applied to construct a pixel-wise representationof local frequency components. We apply our method for object detection inmoving background conditions. Experimental results of our frequency-basedbackground model are evaluated both qualitatively and quantitatively.