Journal of the Korean Society for Industrial and Applied Mathematics

Korean Society for Industrial and Applied Mathematics (한국산업응용수학회)
권호 표지
DOI QR코드

DOI QR Code

A MULTIPHASE LEVEL SET FRAMEWORK FOR IMAGE SEGMENTATION USING GLOBAL AND LOCAL IMAGE FITTING ENERGY

  • Received : 2017.05.02
  • Accepted : 2017.05.29
  • Published : 2017.06.25
Download PDF
⟨ Previous Next ⟩

Abstract

Segmenting the image into multiple regions is at the core of image processing. Many segmentation formulations of an images with multiple regions have been suggested over the years. We consider segmentation algorithm based on the multi-phase level set method in this work. Proposed method gives the best result upon other methods found in the references. Moreover it can segment images with intensity inhomogeneity and have multiple junction. We extend our method (GLIF) in [T. Dultuya, and M. Kang, Segmentation with shape prior using global and local image fitting energy, J.KSIAM Vol.18, No.3, 225-244, 2014.] using a multiphase level set formulation to segment images with multiple regions and junction. We test our method on different images and compare the method to other existing methods.

Keywords

References

  1. D. Mumford and J. Shah, Optimal approximation by piecewise smooth functions and associated variational problems, Communications on pure and applied mathematics, 42 (1989), 577-685. https://doi.org/10.1002/cpa.3160420503
  2. T. Chan and L.A. Vese, Active contours without edges, IEEE Transactions on image processing, 10 (2001), 266-277. https://doi.org/10.1109/83.902291
  3. S. Osher and J.A. Sethian, Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulations, Journal of computational physics, 79 (1988), 12-49. https://doi.org/10.1016/0021-9991(88)90002-2
  4. L.A. Vese and T. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model, International journal of computer vision, 50 (2002), 271-293. https://doi.org/10.1023/A:1020874308076
  5. C.M. Li, C. Kao, J. Gore and Z. Ding, Implicit active contours driven by local binary fitting energy, IEEE transactions on image processing, 17 (2008), 1940-1949. https://doi.org/10.1109/TIP.2008.2002304
  6. C.M. Li, C. Kao, J. Gore and Z. Ding, Minimization of region-scalable fitting energy for image segmentation, IEEE transactions on image processing, 17 (2008), 1940-1949. https://doi.org/10.1109/TIP.2008.2002304
  7. L.Wang, C. Li, Q. Sun, D. Xia and C. Kao, Brain MR image segmentation using local and global intensity fitting active contours/surfaces, Medical Image Computing and Computer-Assisted InterventionMICCAI, 5241 (2008), 384-392.
  8. K. Zhang, H. Song and L. Zhang, Active contours driven by local image fitting energy, Pattern recognition, 43 (2010), 1199-1206. https://doi.org/10.1016/j.patcog.2009.10.010
  9. J.A. Sethian, Level set methods and fast marching methods, Cambridge: Cambridge University Press, 1999.
  10. V. Caselles, F. Catte, T. Coll, and F. Dibos, A geometric model for active contours in image processing, Numerische mathematik, 66 (1993), 1-31. https://doi.org/10.1007/BF01385685
  11. V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contours, International journal of computer vision, 22 (1997), 61-79. https://doi.org/10.1023/A:1007979827043
  12. M. Kass, A. Witkin and D. Terzopoulos, Snakes: active contour models, International journal of computer vision, 1 (1988), 321-331. https://doi.org/10.1007/BF00133570
  13. T.F. Chan and L.A. Vese, Image segmentation using level sets and the piecewise constant Mumford-Shah model, Tech. Rep. CAM 00-14, UCLA Dep. Math, 2000.
  14. C.M. Li, C.Y. Xu, C.F. Gui and M.D. Fox, Level set evolution without re-initialization: a new variational formulation, IEEE Computer Vision and Pattern Recognition, San Diego, (2005), 430-436.
  15. C.M. Li, C.Y. Xu, C.F. Gui and M.D. Fox, Distance regularized level set evolution and its application to image segmentation, IEEE Transactions on image processing, 19 (2010).
  16. H.K. Zhao, T. Chan, B.Merriman and S. Osher, A variational level set approach to multiphase motion, Journal of computational physics, 127 (1996), 179-195. https://doi.org/10.1006/jcph.1996.0167
  17. T. Dultuya, and M. Kang, Segmentation with shape prior using global and local image fitting energy, Journal of the Korean Society for Industrial and Applied Mathematics, 18 (2014), 225-244. https://doi.org/10.12941/jksiam.2014.18.225
  18. J. Lei, M. Lysaker and X.C. Tai, Piecewise constant level set methods and image segmentation, Scale-space and PDEmethods in Computer vision: 5th International Conference, Scale-Space 2005, R.Kimmel, N.Sochen, and J. Weickerts, Eds. Heidelberg, Germany: Springer-Verlag, 3459 (2005), 573-583