摘要： 复杂的计算限制了基于Chan-Vese(C-V)水平集模型的图像分割方法的应用。为提高图像分割的速度，提出一种基于C-V水平集模型的改进水平集方法。在一般情况下，只需要几次简单迭代就能分割出物体的轮廓。实验表明，该方法简单高效，能够快速有效地实现图像轮廓分割。

关键词: 图像分割, Chan-Vese水平集模型, 符号距离函数

Abstract: The complex computing restricts the application of image segmentation method based on Chan-Vese(C-V) level set model. In order to improve the speed of image segmentation, this paper presents a new level set initialization method on C-V model. After a simple iterative, the outline of objects can be separated out. Experiments show that the method is simple and efficient, with good separation effects.

Key words: image segmentation, Chan-Vese(C-V) level set model, signed distance function

中图分类号: 

• TP391