Research of shadow detection strategy based on multi-feature fusion GMM

During the process of accurately segregating an object from background,shadow detection and removal plays an important role.The traditional target and shadow detection algorithms are generally based on single feature information(for example color),which is greatly affected by the change of scene illumination condition,resulting in the decrease of implementation effect of the algorithm.In this paper,a color information and texture information based multi-feature fusion GMM background modelling is proposed to reduce the false detection rate caused by single feature.A double shadow judgment method is proposed to determine the true shadow.The suspected shadow is firstly determined by the color angle,then the shadow is judged again according to the similarity and the deviation of color components between the shadow region and the background.Different shadow detection algorithms are compared,which shows that the double shadow judgment method works well in accurate shadow removal.