[1]胡局新,丁 宾,邵晓根.基于图切的交互式图像分割方法[J].南京师范大学学报(工程技术版),2014,14(04):062.
 Hu Juxin,Ding Bin,Shao Xiaogen.Interactive Image Cut Method Based on Graph Cuts[J].Journal of Nanjing Normal University(Engineering and Technology),2014,14(04):062.
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基于图切的交互式图像分割方法
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
14卷
期数:
2014年04期
页码:
062
栏目:
出版日期:
2014-12-31

文章信息/Info

Title:
Interactive Image Cut Method Based on Graph Cuts
作者:
胡局新丁 宾邵晓根
徐州工程学院信电工程学院,江苏 徐州 221111
Author(s):
Hu JuxinDing BinShao Xiaogen
Department of Information and Electrical Engineering,Xuzhou Institute of Technology,Xuzhou 221111,China
关键词:
图切图像分割最大流/最小割能量函数
Keywords:
graph cutsimage segmentationmax-flow/min-cutenergy function
分类号:
TP391.41
文献标志码:
A
摘要:
图切是一种基于图论的图像分割方法,它基于最大流/最小割定理实现能量函数最小化,其中能量函数的设定、实现的流程等方面可以改进以提高对不同图像的适应性.本文给出了一个基于图切的交互式图像分割方法,用户通过手绘封闭或不封闭线条的方法提供关于前景和背景的先验信息,在此基础上实现图像的分割.首先采用分水岭方法对输入图像进行预分割,把颜色相近的像素分为若干个小区域; 设定合适的能量函数,将预分割的区域之间的颜色相似性、分割结果的平滑性等约束包含在能量函数中,利用求最大流的方法求取使得能量函数最小化的标签集合,从而实现图像的分割.实验证明,本文的方法能快速有效地实现交互式图像分割.
Abstract:
Graph cut is a kind of image segmentation method based on graph theory.Graph cut realizes the minimization of energy based on max-flow/min-cut theorem.In order to make the method more suitable to various images,the energy function and the work flow of the method can be improved.This paper presents an image segmentation method based on graph cuts.In this method,users can present information about foreground and background through hand drawing closed or unclosed curves,and the image segmentation can be further realized based on the information.Watersheds method is first used to pre-segment the input image,and the image is segmented into many small regions based on the color of the pixels.An appropriate energy function is set.The energy function incorporates the color similarity between different regions and smoothness of segmentation result.The label set which makes the energy function minimized is achieved through max-flow method.Thus the image segmentation is completed.The experimental results show that this method can realize interactive image segmentation quickly and effectively.

参考文献/References:

[1] Li Y,Sun J,Tang C K,et al.Lazy snapping[C]//International Conference on Computer Graphics and Interactive Techniques.New York,2004:303-308.
[2]Rother C,Kolmogorov V,Blake A.“GrabCut”:interactive foreground extraction using iterated graph cuts[J].ACM Transactions on Graphics(TOG),2004,23(3):309-314.
[3]Wu Xiaoyu,Wang Yangsheng.Interactive foreground/background segmentation based on graph cut[C]//International Congress on Image and Signal Processing.Sanya,2008.
[4]Boykov Y,Kolmogorov V.An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(9):1 124-1 137.
[5]Boykov Y,Jolly Pi M.Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images[J].ICCV,2001(7):105-112.
[6]Vincent L,Soille P.Watersheds in digital spaces an efficient algorithm based on immersion simulation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1991,13(6):585-598.

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备注/Memo

备注/Memo:
收稿日期:2014-08-16.
通讯联系人:胡局新,硕士,讲师,研究方向:智能信息处理.E-mail:hjx_orange@163.com
更新日期/Last Update: 2014-12-31