目前基于水平集的图像分割方法很难给出基于全局极值的算法终止条件,而大多采用事先设定迭代次数的方法.本文提出了一种改进的Chan-Vese模型,通过添加水平集函数约束项,使得新模型抑制了水平集函数的取值范围,最终收敛至全局极值,并以此作为算法终止条件,无需事先设定迭代次数.实验结果表明,新模型在其终止条件下,分割结果正确,与传统Chan-Vese模型相比,新模型的收敛速度快3～6倍,且通用性更强.
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