Level set is one of active contour models, which is good at handling complex topologies and capturing boundary. The level set methods are specially used in image with intensity inhomogeneity, such as medical image, SAR image, etc. There are many methods based on level set, which are classified into region-based and edge-based. This article firstly derives the function of curve evolution and original model of level set based on region and edge, respectively. Level set methods over the past decade are summed up and categorized. Some typical models and their improvement are introduced in detail. Some level set methods are employed for comparison. The disadvantages and future work are also discussed.

水平集是活动轮廓模型之一，擅长处理复杂的拓扑并捕获边界。水平集方法专门用于强度不均匀的图像，例如医学图像，SAR图像等。基于水平集的方法有很多，分为基于区域的图像和基于边缘的图像。本文首先基于区域和边缘分别推导了曲线演化的功能和水平集的原始模型。总结和分类了过去十年中的水平设置方法。详细介绍了一些典型模型及其改进。使用一些水平集方法进行比较。还讨论了缺点和未来的工作。