Multi-phase image segmentation by the Allen-Cahn Chan-Vese model

被引:8
|
作者
Liu, Chaoyu [1 ]
Qiao, Zhonghua [2 ]
Zhang, Qian [3 ]
机构
[1] Hong Kong Polytech Univ, Dept Appl Math, Hung Hom, Hong Kong, Peoples R China
[2] Hong Kong Polytech Univ, Dept Appl Math & Res Inst Smart Energy, Hung Hom, Hong Kong, Peoples R China
[3] Harbin Inst Technol, Sch Sci, Shenzhen 518055, Peoples R China
关键词
Multi-phase image segmentation; Allen-Cahn Chan-Vese model; Graph Laplacian; Maximum principle; Energy stability; TIME-STEPPING STRATEGY; LEVEL SET MODEL; ACTIVE CONTOURS; SCHEMES; MUMFORD; EFFICIENT; 2ND-ORDER; DYNAMICS; ACCURATE; VARIANT;
D O I
10.1016/j.camwa.2022.12.020
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper proposes an Allen-Cahn Chan-Vese model to settle the multi-phase image segmentation. We first integrate the Allen-Cahn term and the Chan-Vese fitting energy term to establish an energy functional, whose minimum locates the segmentation contour. The subsequent minimization process can be attributed to variational calculation on fitting intensities and the solution approximation of several Allen-Cahn equations, wherein.. Allen-Cahn equations are enough to partition m = 2(n) segments. The derived Allen-Cahn equations are solved by efficient numerical solvers with exponential time integrations and finite difference space discretization. The discrete maximum bound principle and energy stability of the proposed numerical schemes are proved. Finally, the capability of our segmentation method is verified in various experiments for different types of images.
引用
收藏
页码:207 / 220
页数:14
相关论文
共 50 条
  • [1] An Improved Chan-Vese Model for Image Segmentation
    Shi, Yunqiu
    Zhao, Ji
    Yin, Minmin
    INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING BIOMEDICAL ENGINEERING, AND INFORMATICS (SPBEI 2013), 2014, : 67 - 74
  • [2] Chan-Vese model image segmentation with neighborhood information
    Yang, Mingyu
    Ding, Huan
    Zhao, Bo
    Zhang, Wensheng
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2011, 23 (03): : 413 - 418
  • [3] An efficient local Chan-Vese model for image segmentation
    Wang, Xiao-Feng
    Huang, De-Shuang
    Xu, Huan
    PATTERN RECOGNITION, 2010, 43 (03) : 603 - 618
  • [4] Chan-Vese Reformulation for Selective Image Segmentation
    Roberts, Michael
    Spencer, Jack
    JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2019, 61 (08) : 1173 - 1196
  • [5] Chan-Vese Segmentation
    Getreuer, Pascal
    IMAGE PROCESSING ON LINE, 2012, 2 : 214 - 224
  • [6] Topography Image Segmentation Based on Improved Chan-Vese Model
    ZHAO Min-rong
    ZHANG Xi-wen
    JIANG Juan-na
    Computer Aided Drafting,Design and Manufacturing, 2013, (02) : 13 - 16
  • [7] The Chan-Vese Model With Elastica and Landmark Constraints for Image Segmentation
    Song, Jintao
    Pan, Huizhu
    Liu, Wanquan
    Xu, Zisen
    Pan, Zhenkuan
    IEEE ACCESS, 2021, 9 : 3508 - 3516
  • [8] Completely Convex Formulation of the Chan-Vese Image Segmentation Model
    Ethan S. Brown
    Tony F. Chan
    Xavier Bresson
    International Journal of Computer Vision, 2012, 98 : 103 - 121
  • [9] Generalized Chan-Vese Model for Image Segmentation with Multiple Regions
    Dang Tran Vu
    Tran Thi Thu Ha
    Song, Min Gyu
    Kim, Jin Young
    Choi, Seung Ho
    Chaudhry, Asmatullah
    LIFE SCIENCE JOURNAL-ACTA ZHENGZHOU UNIVERSITY OVERSEAS EDITION, 2013, 10 (01): : 1889 - 1895
  • [10] Completely Convex Formulation of the Chan-Vese Image Segmentation Model
    Brown, Ethan S.
    Chan, Tony F.
    Bresson, Xavier
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2012, 98 (01) : 103 - 121