期刊文献+

一种结合图割与双水平集的图像分割方法 被引量:8

Image segmentation approach based on graph cuts and dual level set method
下载PDF
导出
摘要 针对水平集方法在图像分割中需要多次迭代,且计算量大的问题,提出一种基于图割与双水平集的图像分割方法。首先在目标边界内外部各设置一条初始轮廓线和一个阈值,通过双水平集方法对轮廓线进行演化。当轮廓线的能量变化率小于给定阈值时,终止水平集演化。将得到的两条轮廓线化为源点和汇点,通过图割方法得到最终目标边界。该方法有效减少了水平集迭代次数,提高了分割效率,而且给出了一种终止水平集迭代的方式。实验表明该方法具有较好的分割效果和较高的分割效率。 Taking into account the problem that level set method for image segmentation requires more iterations and needs more computing time,a new method based on graph cuts and dual level set has been introduced.First of all,inside and outside of the boundary of the object set an initial contour separately and a threshold,and evolve the two contours by level set method.When the change rate of the contour is less than the given threshold,terminate the evolution.Then the two contours will be as source and sink,and obtained the final edge by graph cuts.This approach reduces the level set iterations,thus improves the efficiency for segmentation,and provides a way to end the level set iteration.Experiments show that the method has better effect and higher efficiency for segmentation.
出处 《计算机工程与应用》 CSCD 2012年第3期195-197,201,共4页 Computer Engineering and Applications
基金 国家自然科学基金(No.40671133) 中央高校基本科研业务费专项资金(No.GK200902015)
关键词 水平集方法 图割 图像分割 level set method graph cuts image segmentation
  • 相关文献

参考文献10

  • 1Osher S,Sethian J.Fronts propagating with curvature dependent speed:algorithms based the Hamilton Jacobi formulation[J].Jour- hal of Computational Physics, 1998,79 ( 1 ) : 12-49.
  • 2Adalsteinsson D, Sethian J A.Fast level set method for propagat- ing interfaces[J].Journal of Computer Physics, 1995,118 (2) : 269-277.
  • 3Li Chunming.Level set evolution without re-initialization:a new variational formulation[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2005.
  • 4Wu Z,Leahy R.An optimal graph theoretic approach to data clus- tering:theory and its application to image segmentation[J].lEEE Transactions on Pattem Analysis and Machine Intelligence, 1993, 15(11):1101-1113.
  • 5Kolmogorov V, Zabih R.What energy functions can be minimized via graph cuts?[C]//Proceedings of European Conference on Com- puter Vision,2002:65-81.
  • 6Xu Ning, Ahuja N, Bansal R.Object segmentation using graph cuts based active contours[J].Computer Vision and Image Understand- ing, 2007,107 : 210-224.
  • 7Sethian J A.Fast marching level set methods for three dimen- sional photolithography development[C]//Proceeding of SPIE, San Diego, CA, USA, 1996,2726: 261-272.
  • 8Tsitsiklis J.Efficient algorithms for globally optimal trajectories[J]. IEEE Transactions on Automatic Control, 1995,40(9) ; 1528-1538.
  • 9Boykov Y,Kolmogorov V.An experimental comparison of Min- Cut/Max-Flow algorithms for energy minimization in vision[J]. IEEE Transactions on PAMI, 2004,26:1124-1137.
  • 10Boykov Y, Jolly M.Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images[C]//Proceed- ings of IEEE International Conference on Computer Vision,2001, 1 : 105-112.

同被引文献73

  • 1杨帆,廖庆敏.基于图论的图像分割算法的分析与研究[J].电视技术,2006,30(7):80-83. 被引量:16
  • 2MALLADI R,SETHIAN J A,VEMURI B C. Shape modeling with front propagation: a level set approach [ J ]. IEEE Trans. Pattern Analysis and Machine Intelligence, 1995,17 (2) : 158-175.
  • 3KASS M ,WITKIN A ,TERZOPOULOS D. Snakes : active contour models [J]. International Journal of Computer Vision,1988,1 (4) :321-331.
  • 4CHAN T F,VESE L A. Active contours without edges[J]. IEEE Trans. Image Processing,2001,10( 2 ) :266-277.
  • 5LI C,XU C,GUI C,et al. Level set evolution without re-initialization:a new variational formulation[ C ]//Proc. 1EEE Computer Society Confer- ence on Computer Vision and Pattern Recognition. San Diego: IEEE Press,2005 : 1-7.
  • 6NING X, AHUJA N, BANSAL R. Object segmentation using graph cuts based active contours [ J]. Computer Vision and Image Understanding, 2007,107 (3) :210-224.
  • 7MUNFORD D, SHAH J. Optimal approximations by piecewise smooth functions and associated variational problems [ J ]. Communications on Pure and Applied Mathematics, 1989,42(5 ) :577-685.
  • 8FORD L R,FULKERSON D R. Maximal flow through a network[ J]. Canadian Journal of Mathematics, 1956,8 (3) :399-404.
  • 9BOYKOV Y,JOLLY M P. Interactive graph cuts for optimal boundary& region segmentation of objects in N-D images [ C ]//Proc. International Conference on Computer Vision. Vancouver: [ s. n. ] ,2001:105-112.
  • 10Kolmogorov V, Boykov Y. What metrics can be approximated by geo-cuts , or global optimization of length / area and flux [R]. Beijing: ICCV, 2005: 564-571.

引证文献8

二级引证文献11

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部