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一个基于图形的高效图像分割算法，包括论文及相应的源代码。-This paper addresses the problem of segmenting an image into regions. We define a predicate for
measuring the evidence for a boundary between two regions using a graph-based representation of the image. We
then develo
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这是基于图论的图像分割源代码，效果很好，欢迎下载.-This is based on graph theory image segmentation source code, works well, welcome to download.
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这个代码是文章Efficient Graph-Based Image Segmentation的实现，结合了vs2008和opencv，该算法进行分割，速度很快，效果不错。-The source code is an implementation of the paper: Efficient Graph-Based Image Segmentation. VS2008 and Opencv are combined in the implementation process.
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Graph cut Image Segmentation
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Efficient Graph-Based Image Segmentation
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（转）vc 的 图像分割
命令行 格式：
segment 0.5 300 50 17.ppm 17out.ppm-(Transgenic) vc the command-line format for image segmentation: segment 0.5 300 50 17.ppm 17out.ppm
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Efficient Graph-Based Image Segmentation 一篇论文的代码，修改后，在VS2008运行环境下编译通过-Efficient Graph-Based Image Segmentation paper code, revised in the operating environment under the VS2008 compiler through
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Effcient Graph-Based Image Segmentation算法的源码， 已通过测试， 可以使用-the source data of the algoritham Effcient Graph-Based Image Segmentation
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一种改进的图象分割程序,分割出来效果相当好,尤其对于丰富的图象,保证别人没有上传过-Based on graph cut image segmentation algorithm, split the result was very good, especially for texture-rich images, ensure that no one else uploaded
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Otsu算法是图像分割算法中比较实用和高效的一种，对图像的后续处理有很好的作用-Otsu algorithm is image segmentation algorithm in a more practical and efficient, the follow-up processing of the images have a good effect
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image segmentation: introduction of graph cut, grab cut, normalize cut,-image segmentation: introduction of graph cut, grab cut, normalize cut,...
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efficient Graph-Based image Segmentation C++ code(with visual 2008)
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基于图论的图像分割，使用区域之间和区域内部进行比较的准则，对于风景图片效果不错。-Graph-based image segmentation, using the region based comparison criteria, good for scene images.
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this program for efficient graph based image segmentation
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为了提高算法的执行效率, 应用粒子群算法求取图像中任意两点间最短路径来定位目标边界, 并与经典的基于Dijkstra 动态规划图搜索的Liv e Wire 算法进行比较.-In order to improve the efficiency of the algorithm, particle swarm algorithm to strike any of images to locate the shortest path between two object boundaries, and
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五种当前主要的基于图的图像分割方法（normalized cut, min-cut/max-flow, isoperimetric partitioning, minimum spanning tree and random walker）的论文原文。-The original papers of five main graph-based image segmentation methods. They are normalized cut, min-cut/max-flow, isoperi
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基于graph cuts的图像分割的示例-Image segmentation based on graph cuts the sample
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下面这个论文描述的分割算法的实现：
Efficient Graph-Based Image Segmentation
Pedro F. Felzenszwalb and Daniel P. Huttenlocher
International Journal of Computer Vision, 59(2) September 2004.
这个程序使用彩色图像（PPM格式）并为产生的分割结果的每个区域随机分配颜色。-Implementation of the seg
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Efficient Graph-Based Image Segmentation & k-means Image Segmentation
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this program for efficient graph based image segmentation
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