为扩大参数活动轮廓模型外力场的捕获范围，消除噪声对弱边界分割的影响，文中结合参数活动轮廓模型和卷积向量场的优点，提出了一种新的参数活动轮廓模型．该模型通过 Harris 矩阵得到梯度图像，依据局部区域的均值和方差估计噪声的概率，进而确定参数活动轮廓模型和卷积向量场的作用权重，最后得到一个全局向量场．合成梯度图像和医学图像的仿真实验结果表明，文中模型能够准确地分割出图像目标，具有一定程度的抗噪性．

In order to extend the capture range of the external force field in the parametric active contour model and to eliminate the effect of the noise on the segmentation with weak edges,this paper proposes a novel parameter active contour model by combining the advantages of the parameter active contour with those of the vector field con-volution.In this model,first,an edge image is obtained through Harris matrix,and the probability of the noise is estimated according to the mean and variance in a local region.Then,the weights of both the parameter active con-tour and the vector field convolution are determined.Finally,a global vector field is achieved.Simulation results of synthetic edge images and medical images indicate that the proposed method can accurately segment objects and can resist noises to a certain degree.