Color snakes
Color snakes
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DOI：
10.1006/cviu.1997.0562
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发表时间：
1997-11-01
影响因子：
4.5
通讯作者：
Sapiro, G
中科院分区：
文献类型：
--
作者：
Sapiro, G
本文提出了一种矢量图像目标分割的框架。第一种方法是基于几何活动轮廓线向待检测目标移动的方法。对象边界作为测地线或最小加权距离曲线获得，其中度量由向量值数据中的边缘的定义给出。曲线流对应的主动轮廓持有正式的存在性，唯一性，稳定性和正确性的结果。该方案自动处理变形曲线拓扑中的更改。该技术是适用的，例如，颜色和纹理图像以及多尺度表示。然后，我们提出了这些矢量活动轮廓的扩展，提出了一个可能的图像流矢量值图像分割。该算法是基于移动的每一个图像水平集，根据建议的矢量主动轮廓。该扩展还显示了活动轮廓和一些基于偏微分方程的图像处理算法（如各向异性扩散和冲击滤波器）之间的关系。(C)北京：科学出版社.
A framework for object segmentation in vector-valued images is presented in this paper. The first scheme proposed is based on geometric active contours moving toward the objects to be detected in the vector-valued image. Object boundaries are obtained as geodesics or minimal weighted-distance curves, where the metric is given by a definition of edges in vector-valued data. The curve flow corresponding to the proposed active contours holds formal existence, uniqueness, stability, and correctness results. The scheme automatically handles changes in the deforming curve topology. The technique is applicable, for example, to color and texture images as well as multiscale representations. We then present an extension of these vector active contours, proposing a possible image flow for vector-valued image segmentation. The algorithm is based on moving each one of the image level sets according to the proposed vector active contours. This extension also shows the relation between active contours and a number of partial-differential-equations-based image processing algorithms as anisotropic diffusion and shock filters. (C) 1997 Academic Press.