Shadow removal algorithm based on Gaussian mixture model

Abstract

Shadow removal is one of the most important parts of moving object detection in the field of intelligent video since the shadow definitely affects the recognition result.In terms of the disadvantage of shadow removal methods utilizing texture,a new algorithm based on Gaussian Mixture Model(GMM) and YCbCr color space was proposed.Firstly,moving regions were detected using GMM.Secondly,the Gaussian mixture shadow model was built through analyzing the color statistics of the difference between the foreground and background of the moving regions in YCbCr color space.Lastly,the threshold value of the shadow was obtained according to the Gaussian probability distribution in YCbCr color space.More than 70 percent of shadow pixels in sequence images of the experiments could be detected by the algorithm accurately.The experimental results show that the proposed algorithm is efficient and robust in object extraction and shadow detection under different scenes.