Segmentation of motion objects based on graph cuts and C-V model;
将两种基于图论的算法图切割与随机游走应用于运动对象的分割。
The empirical research shows that the C-V model with negative area parameter can segment some images that the original C-V model is not applicable to.
实验研究表明：面积项系数取负值时，C - V模型能够分割某些原来不适用的图像。
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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