基于主动轮廓模型和水平集方法的图像分割技术

图像分割是计算机底层视觉中首要解决的关键问题。为了使人们对该领域现状有个概略了解。首先回顾了近十几年来基于主动轮廓模型的图像分割技术的发展概况；然后分类介绍了基于边界、基于区域和基于边界与区域的主动轮廓模型技术的演变及各自的优缺点，以及相应的能处理轮廓拓扑变化的稳定数值求解方法——水平集方法；最后展望了主动轮廓模型在图像对准中的应用。

A Survey on Image Segmentation Using Active Contour and Level Set Method

Image segmentation is a classical and crucial problem in the fields of computer vision and image understanding. This paper gives a review on the variation based active contour model and level set method developed in recent years for image segmentation. The basic ideas of three types of active contour models, i. e. , edge based, region based and edge- region based models, are presented, their advantages and disadvantages are summarized, and a number of improvements are analyzed in detail. The level set method, which is numerically stable and capable of describing the topology change of the contour, is briefly introduced as an advanced numeric algorithm to solve these models. Finally, the potential application of active contour in image registration is discussed.