Motion detection based on the combining of the background subtraction and the structure–texture decomposition

Abstract

To detect the moving objects in a video sequence based on background subtraction approaches, a background model should be estimated at the first time before subtract it from each image of the sequence and then segmenting the moving objects. In this paper, we present a new approach based on the combining of the background subtraction and the structure–texture decomposition (BS–STD). First, each gray-level image of the sequence will be decomposed on two components, structure and texture/noise by applying the Osher and Vese algorithm. The structure component of each image of the sequence will be taken to generate the background model using the median filter. The absolute difference used to subtracting the background before compute the binary image of the moving objects using the threshold generated by Otsu's method. The structure–texture decomposition (STD) is also used to ameliorate the results of methods, the background estimation algorithm with Σ−Δ (SDE), Simple Statistical Difference (SSD) and Motion detection with pyramid structure of background model (MDPS). The experimental results demonstrate that our approach is effective and accurate for moving objects detection and the structure–texture decomposition adds improvements to the results of state-of-the-art methods.