Image segmentation based on improved Chan-Vese model

YANG Ming-yu

doi:10.3788/YJYXS20142903.0473

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Image segmentation based on improved Chan-Vese model

更新时间：2020-08-12

- Image segmentation based on improved Chan-Vese model
- Chinese Journal of Liquid Crystals and Displays Vol. 29, Issue 3, Pages: 473-478(2014)
- 作者机构：
  
  中国科学院长春光学精密机械与物理研究所, 中国科学院航空光学成像与测量重点实验室, 吉林长春 130033
- 作者简介：
- 基金信息：
- DOI：10.3788/YJYXS20142903.0473
  CLC： TP391.4
- Received：17 January 2014，
  
  Revised：18 February 2014，
  
  Published：25 April 2014
- 稿件说明：
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杨名宇. 基于改进Chan-Vese模型的图像分割[J]. 液晶与显示, 2014,29(3): 473-478

YANG Ming-yu. Image segmentation based on improved Chan-Vese model[J]. , 2014,29(3): 473-478
杨名宇. 基于改进Chan-Vese模型的图像分割[J]. 液晶与显示, 2014,29(3): 473-478 DOI： 10.3788/YJYXS20142903.0473.

YANG Ming-yu. Image segmentation based on improved Chan-Vese model[J]. , 2014,29(3): 473-478 DOI： 10.3788/YJYXS20142903.0473.

摘要

目前基于水平集的图像分割方法很难给出基于全局极值的算法终止条件，而大多采用事先设定迭代次数的方法。本文提出了一种改进的Chan-Vese模型，通过添加水平集函数约束项，使得新模型抑制了水平集函数的取值范围，最终收敛至全局极值，并以此作为算法终止条件，无需事先设定迭代次数。实验结果表明，新模型在其终止条件下，分割结果正确，与传统Chan-Vese模型相比，新模型的收敛速度快3~6倍，且通用性更强。

Abstract

Most methods based on level set do not have the stop criterion based on the global minimum

instead they employ the iteration number as stop criterion. This paper proposes an improved Chan-Vese model

by adding a constrained term

making the functional converge to global minimum

and presents the stop criterion based on global minimum

without setting iteration number in advance. Experimental results show that the proposed model can segment images correctly under the new stop criterion. Compared with the Chan-Vese model

it has a faster convergence

3~6 times faster than Chan-Vese model

and is of good general use.

关键词

Keywords

references

Kass M, Witkin A, Terzopoulos D. Snakes: Active contour models [J].International Journal of Computer Vision,1988, 1(4): 321-332.[2] 王醒策,张美霞,武仲科,等. 基于全局LBF水平集模型的脑血管层次粗分割[J]. 光学精密工程, 2013,21(12): 3283-3297. Wang X C, Zhang M X, Wu Z K. Level coarse brain vessel segmentation based on global LBF model [J].Opt. Precision Eng.,2013, 21(12): 3283-3297. (in Chinese)[3] 王卫星,苏培垠. 基于颜色、梯度矢量流活动轮廓及支持向量机实现白细胞的提取和分类[J]. 光学精密工程, 2012, 20(12): 2781-2790. Wang W X, Su P Y. Blood cell image segmentation on color and GVF snake for Leukocyte classification on SVM [J].Opt. Precision Eng.,2012, 20(12): 2781-2790. (in Chinese)[4] Chunming L, Chiu-Yen K, Gore C, et al.Minimization of region-scalable fitting energy for image segmentation [J].IEEE Trans. Image Processing,2008, 17(10): 1940-1949.[5] 田丰,夏雪,王鹤. 真三维显示在医学教育与仿真中的应用[J]. 液晶与显示, 2012,27(4): 535-538. Tian F, Xia X, Wang H. Applications of volumetric three-dimensional display in medical simulation and education [J].Chinese Journal of Liquid Crystals and Displays,2012, 27(4):535-538.(in Chinese)[6] 张麟,汪源源,王威琪,等. 活动轮廓模型和Contourlet多分辨率分析分割血管内超声图像[J]. 光学精密工程, 2008, 16(11): 2303-2311. Zhang L, Wang Y Y, Wang W Q, et al.Intravascular ultrasound image segmentation based on active contour model and contourlet multiresolution analysis [J].Opt. Precision Eng.,2008, 16(11): 2303-2311. (in Chinese)[7] Malladi R, Sethian J A, Vernuri B C. Shape modeling with front propagation: A level set approach [J].IEEE Trans. Pattern Analysis and Machine Intelligence,1995, 17(2): 158-175.[8] Caselles V, Kimmel R, Sapiro G. Geodeisic active contours [J].International Journal of Computer Vision,1997, 22(1): 61-79.[9] Sethian J A.Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science [M].London: Cambridge University Press, 1999.[10] Osher S, Sethian J A. Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulation [J].Journal of Computer Physics,1988, 79(1): 12-49.[11] Mumford D, Shah J. Optimal approximation by piecewise smooth functions and associated variational problems [J].Comm. Pure Appl. Math.,1989, 42(5): 577-685.[12] Chan F, Vese L. Active contours without edges [J].IEEE Trans. Image Processing,2001, 10(2): 266-177.[13] Chan F, Esedoglu S, Nikolova M. Algorithms for finding global minimizers of image segmentation and denoising models [J].SIAM J. Appl. Math.,2006, 66(5): 1632-1648.[14] Bresson X, Esedoglu S, Vandergheynst P, et al.Global minimizer of the active contour/snake model [J].J.Math. Image Vis.,2007, 28(1): 151-167.

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