为了准确提取出感兴趣区域的边界，研究出一种具有拓扑自适应性的图象两步分割方法，即基于棱边检测算子的B样条活动围道分割方法，该方法首先是进行图象的底层分割，即用基于图象局部特性（像元邻域）操作的棱边检测算子来检测图象的棱边点，然后进行图象的高层分割，即用基于图象全局统计特性的B样条活动围道分割方法来求取对象的准确边界，另外，还提出了基于区域欧拉数的拓扑自适应处理方案，该两图像分割方法具有人为干预少，对初始条件不敏感，拓扑自适应性强等优点，试验结果证明了该方法的有效性。

This paper proposes a hierarchical method of image segmentation with topological adaptability, called B spline active contour based on edge detector. Unlike traditional method of active contour, our method takes region homogenous property into account and designs a new external force regional force, which is very robust to noise contamination. Also, internal force is integrated into the B spline. Our method is composed of two steps. First step is a kind of low level image segmentation. In this step, a local edge detector is used for detecting all edge points of the image. Second step is a kind of high level image segmentation. In this step, our B spline active contour based on the global image statistic is used for refining the region boundary. Also, we propose a new topology adaptability method, which is based on the change of region Euler number. Our method requires less interactive operation and is insensitive to initial condition. The experiments reported in the paper, performed on real images, confirm that the method can offer a good segmentation result and it has a very good topological adaptability.