To improve the segmentation performance, a novel approach for shadow detection integrating multiple features was proposed, which considers information of color, shading, texture, neighborhoods and temporal consistency to detect shadows in a scene. Firstly, illumination logarithm invariability of neighborhood shadow pixel was proposed to detect shadow. Then, integrating the shadow feature of HSV color space and the statistical feature in a region with the combined blocks based on a gradient algorithm, the shadow was detected efficiently and reliably. Finally, an improved quantitative method was introduced to evaluate the algorithm on a bench mark suite of different illumination and environment video sequences. The experimental results show the effective performance of the algorithm. The method can be applied to moving target segmentation in intelligent video surveillance.