Abstract: Image segmentation method based on GrabCut has a high time complexities in the stage of estimating the GMM iteratively and it is prone to produce segmentation errors when the image include noise or shelter.To improve these problems,an algorithm combining GMM with muti-sampling and adaptive shape priors is proposed in this paper.First,the image pixels are muti-sampled based on the sampling theorem and the GMM parameters are estimated with samples.Then the shape priors are applied to constrain the process of image segmentation and the constraint is controlled adaptively.Finally the segmentation results are obtained.This paper handles the affine transformation of shape by using the method of SURF and RANSAC,in order to make this algorithm flexibility.The experiments show that segmentation accuracy and efficiency are improved in the algorithm.