Compared with traditional image segmentation methods, C-V model has some special advantages: it can accommodate itself to the changes of the object's Geometric topology and obtain continuous boundary.
因而C -V模型具有其它传统图像分割方法不具备的许多优点：它可以自动适应目标几何结构的拓扑变化，获得连续边缘。
Compared with traditional image segmentation methods, C-V model has some special advantages: it can accommodate itself to the changes of the object's Geometric topology and obtain continuous boundary.
因而C -V模型具有其它传统图像分割方法不具备的许多优点：它可以自动适应目标几何结构的拓扑变化，获得连续边缘。
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