传统的基于向量场的活动轮廓模型不能准确地提取复杂形状边界，尤其当初始轮廓曲线在目标边界外部、提取复杂的凹形边界时，常遇到“平衡点” 问题．为此，文中提出了基于多阶段向量场的活动轮廓模型．首先在离散化的轮廓曲线上取一些样本点，并按其法线方向将它们映射到目标特征点; 然后由传统向量场和映射产生的向量场得到一个加权平均的向量场，将轮廓曲线在该向量场中演化，若轮廓曲线未完全收敛到边界，则在未收敛的轮廓曲线上取新样本点，按前面方法计算出新的向量场．经过在多阶段向量场中的演化，轮廓曲线最终收敛到目标边界．实验结果表明，相比于传统方法，文中方法更有效．

 During the extraction of boundary with complex geometry,no accurate results can be obtained by the tra-ditional active contour models based on the vector field,and,especially,equilibrium issues may occur during the extraction of complex concavity whose initial contour is outside the object.In order to solve these problems,an active contour model based on the multistage vector field is proposed.In this model,first,several points are sam-pled on the discrete active contour and mapped to object feature points according to the normal of sample points.Then,a weighted mean vector field,in which the contour evolves,is derived from the vector field obtained via the mapping and the traditional vector field.If the contour does not completely converge to the boundary,new points are sampled on the unconverged contour,and a new vector field is then obtained through the same steps as above.Thus,the contour converges to the object boundary after evolving in several stages of the vector field.Experimental results show that the proposed method is more effective than the traditional ones.