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clip_graph
- 本源码给出了实现线段和矩形的裁剪算法. 包含有一\"图形裁剪\"文件夹 实验步骤的简要提示的WORD文档--Grphics experiment NO4-图形裁剪.doc 一可执行文件-- 图形裁剪.exe - The source code has produced the realization line segment and the rectangle cuts out the algorithm Contains has a \"graph to cut out
SWImage
- The Swendsen-Wang Cuts algorithm is used to label atomic regions (superpixels) based on their intensity patterns using generative models in a Bayesian framework. The prior is based on areas of connected components, which provides a clean segmentation
matlabGrabCutS
- graphcuts算法，MATLAB编写，可以运行，能直观看到结果。-graph cuts algorithm，MATLAB prepared
GaussianMixture
- source code for graph cuts in computer vision
grabcut
- 用grabcut算法对图像进行分割，程序支持mask和矩形框两种输入，并附有样图和结果图。详细原理请参考文献： GrabCut - Interactive Foreground Extraction using Iterated Graph Cuts-Grabcut algorithm is for image segmentation. the program supports two input mask and a rectangular box, along with sample di
Background
- This is an incomplete implementation shared for illustrative purposes only. The section implementing graph cuts for minimization is not included.
GRAPH__CUT
- 实现了Yuri Y. Boykov论文中最简单的图割算法(vs2013)-graph-cuts algorithm,writing accoding to the aritcle that Yuri Y. Boykov public lished (vs2013)
Lazy_Grab_cut
- 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.
matlab
- 立体匹配中常用的方法，图割（graph cut），用到了a扩展及交换，程序涉及matlab及c-Stereo matching methods commonly used, graph cuts (graph cut), and uses a extended exchange program involving matlab and c++
IGC_Software
- 通过区域迭代合并与定位切图的图像分割算法，非常好的。-Image Segmentation by Iterated Region Merging with Localized Graph Cuts
segment
- 一个学生写的Graph Cuts算法用于分割的OpenCV实现-Graph Cuts Segmentation in OpenCV
Boykov的GraphCut算法
- Boykov的GraphCut算法 Graph cuts是一种十分有用和流行的能量优化算法，在计算机视觉领域普遍应用于前背景分割（Image segmentation）、立体视觉（stereo vision）、抠图（Image matting）等。(Boykov GraphCut As applied in the field of computer vision, graph cuts can be employed to efficiently solve a wide var
Image-Stitching-using-Graphcut-master
- 运行image_synthesis.m，两个参数分别为第一幅图片和第二幅图片，输出结果为合成后的图片(Running image_synthesis.m, the two parameters are the first picture and the second picture, the output result is the synthesized picture)