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实现最小割，基于图的图像分割算法，学习必备。-Minimum cut graph-based image segmentation algorithm, learning essential.
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基于图论的图像分割——最大流最小割算法。内含最大流最小割算法通用matlab程序。-Maximum flow minimum cut algorithm- based on graph theory image segmentation. Maximum flow minimum cut algorithm contains generic matlab program.
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与以往关注图像局部特征和局部连续性的方法不同，本文中的方法能够提取关于图像的全局印象。为此，我们将图像分割问题转化为图划分问题并提出了划分中的一种全局判别准则——Ncut (Normalized Cut)-Concerned with the past image local characteristics and continuity of local methods, the methods herein can extract images on the overall impressio
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Normalized Cut Image Segmentation Code，一种基于图的图像分割算法源代码，效果较好，但运行速度不是很高，可供图像分割初学者学习-Normalized Cut Image Segmentation Code, a graph based image segmentation algorithm
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一个新的求图的最小割的方法，Stoer-Wagner能够求得最佳分割方式，而且其速度很快。
-A new method for the minimum cut of the graph, Stoer-Wagner is able to get the best segmentation method, and its speed is very fast.
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grab_cut,graph gut的进阶版，运用了lazy snapping-There are advanced segmentation algorithms in the literature which extends the concepts of graph cuts. Most prominent of them are Graph cuts and Lazy Snapping. Lazy napping is an interactive image cut out tool.
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基本的图割法进行图像分割，效果较好，思路清晰(The graph cut method is used for image segmentation, and the effect is bette)
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