Abstract:Considering the contradiction of real-time and accuracy in existing shadow detection method, this paper presents a new shadow detection method, the method combines color feature and texture feature by weight fusion. Firstly, we use HSV color information to extract the suspected shadow points. Secondly, we calculate the shadow brightness membership according to the brightness ratio, then judge the points with high brightness membership as real shadow points, so we can reduce the calculation of texture detection. For those suspected shadow points with low brightness membership, we extract the CS-LBP texture of these points, because CS-LBP is highly efficient. Via matching texture, we calculate the texture membership according to the level of similarity of textures and distribution of shadow. At last, considering the fact that texture change with the brightness, we put forward the method of feature texture membership by weight fusion, and this weight self-adapts to the brightness ratio. Experiment results show that, the proposed method has a good real-time performance, it can remove the self-shadows, and performs better accuracy in segmentation.With using membership, the proposed method is more robust to noise and illumination changes.