A novel multi-layer level set method for image segmentation

Journal of Universal Computer Science

Volumn 14, Issue 14, 2008, Pages 2428-2452

  Wang, Xiao Feng ^a,b,c   Huang, De Shuang ^a  

^a INSTITUTE OF INTELLIGENT MACHINES   (China)

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c HEFEI UNIVERSITY   (China)

Author keywords

Curve evolution; Image layer; Level set; Multi layer; Segmentation; Termination criterion

Indexed keywords

EID: 57549114286     PISSN: 0958695X     EISSN: 09486968     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (28)

1. Adams, R. and Bischof, L.: Seeded region growing, IEEE Trans. Pattern Anal. Mack Intell., 16(6): 641-647, Jun. 1994.
2. Allaire, G. and Jouve, F. A.: A level-set method for vibration and multiple loads structural optimization, Comput. Meth. Appl. Mech. Eng., 194: 3269-3290, 2005.
3. Chan, T. F. and Vese, L. A.: Active contours without edges, IEEE Trans. Image Process., 10(2): 266-277, Feb. 2001.
4. Chang, Y. and Li, X.: Adaptive image region-growing, IEEE Trans. Image Process., 3(6): 868-872, Nov. 1994.
5. Chaudhury, K. N. and Ramakrishnan, K. R.: Stability and convergence of the level set method in computer vision, Pattern Recognition Letters., 28(7): 884-893, 2007.
6. Engquist, B., Tornberg, A.K. and Tsai, R.: Discretization of Dirac delta functions in level set methods, J. Comput. Phys., 207(1): 28-51, 2005.
7. Hijjatoleslami, S. A. and Kitter, I.: Region growing: a new approach, IEEE Trans. Image Process., 7(7): 1079-1084, Jul. 1998.
8. Jeon, M., Alexander, M., Pedrycz, W. and Pizzi, N.: Unsupervised hierarchical image segmentation with level set and additive operator splitting, Pattern Recognition Letters., 26: 1461-1469, 2005.
9. Kass, M., Witkin, A. and Terzopoulos, D.: Snakes: Active contour models, Int. J. Comput. Vision., 1(4): 321-331, 1987.
10. Lee, S. H. and Seo, J. K.: Level set-based bimodal segmentation with stationary global minimum, IEEE Trans. on Image Process., 15(9): 2843-2852, 2006.
11. Linda, G. S. and George, C. S.: Computer Vision., New Jersey: Prentice-Hall, 2001.
12. Lin, Y. W. and Lee, S. U.: On the color image segmentation algorithm based on the thresholding and the fuzzy C-means techniques, Pattern Recognition., 23(9): 935-952, 1990.
13. Malladi, R., Sethian, J. A. and Vemuri, B. C.: Shape modeling with front propagation: A level set approach, IEEE Trans. Pattern Anal. Mach. Intell., 17(2): 158-175, 1995.
14. Mumford, D. and Shah, J.: Optimal approximation by piecewise smooth functions and associated variational problems, Commun. Pure Appl. Math., 42: 577-685, 1989.
15. Osher, S. and Sethian, J. A.: Fronts Propagating with Curvature-Dependent Speed: Algorithms Based on Hamilton-Jacobi Formulations, J. Comput. Phys., 79(1): 12-49, 1988.
16. Palmer, P. L., Dabis, H. and Kitler, J.: A performance measure for boundary detection algorithms, Computer Vision and Image Understanding., 63(3): 476-494, 1996.
17. Sethian, J. A.: Level set methods and fast marching methods., Cambridge University Press, 1996.
18. Shi, J. and Malik, J.: Normalized cuts and image segmentation, IEEE Trans. Pattern Anal. Mach. Intell., 22(8): 888-905, Aug. 2000.
19. Sonka, M., Hlavac, V. and Boyle, R.: Image Processing, Analysis and Machine Vision, Second Edition., Beijing: Posts & Telecom Press, 2002.
20. Towers, J.: Two methods for discretizing a delta function supported on a level set, J. Comput. Phys., 220: 915-931, 2007.
21. Tsai, A., Yezzi, A. and Willsky, A. S.: Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification, IEEE Trans. Image Process., 10(8): 1169-1186, 2001.
22. Tsai, Y. H.: Rapid and accurate computation of the distance function using grids, J. Comput. Phys., 178(1): 175-195, 2002.
23. Tsai, Y. H. and Osher, S.: Total Variation and Level Set Based Methods in Image Science, Cambridge University Press, Acta Numerica., 1-61, 2005.
24. Urquhart, R.: Graph theoretical clustering based on limited neighborhood sets, Pattern Recognition., 15(3): 173-187, 1982.
25. Vese, L. A. and Chan, T. F.: A multiphase level set framework for image segmentation using the Mumford and Shah Model, Int. J. Comput. Vision., 50(3): 271-293, 2002.
26. Weber, M., Blake, A. and Cipolla, R.: Initialisation and termination of active contour level-set evolutions, In Proc. 2nd IEEE workshop on Variational, Geometric and Level Set Methods in Computer Vision., 161-168, 2003.
27. Xu, C. and Prince, J. L.: Snakes, shapes, and gradient vector flow, IEEE Trans. Image Process., 7(3): 359-369, Mar. 1998.
28. Li, J., Yang, X. and Shi, P. F.: A fast level set approach to image segmentation based on Mumford-Shah model, Chinese Journal of Computers., 25(11): 1175-1183, 2002.