Summary
In this chapter, we will review the current state of knowledge on regionbased digital image segmentation methods. More precisely, we will concentrate on the four families of such algorithms: (a) The leading theme here will be the framework of fuzzy connectedness (FC) methods. (b) We will also discuss in detail the family of graph cut (GC) methods and their relations to the FC family of algorithms. The GC methodology will be of special importance to our presentation, since we will emphasize the fact that the methods discussed here can be formalized in the language of graphs and GCs. The other two families of segmentation algorithms we will discuss consist of (c) watershed (WS) and (d) the region growing level set (LS) methods. Examples from medical image segmentation applications with different FC algorithms are also included.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
- Image Segmentation
- IEEE Trans Pattern Anal
- Strong Path
- Auxiliary Data Structure
- Image Intensity Function
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
J. Udupa, S. Samarasekera, Graph Models Image Process. 58(3), 246 (1996)
P. Saha, J. Udupa, Comput. Vis. Image Underst. 82(1), 42 (2001)
J. Udupa, P. Saha, R. Lotufo, IEEE Trans. Pattern Anal. Mach. Intell. 24, 1485 (2002)
P. Saha, J. Udupa, in Proceeding of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, pp. 28–35 (2002)
K. Ciesielski, J. Udupa, P. Saha, Y. Zhuge, Comput. Vis. Image Underst. 107(3), 160 (2007)
Y. Zhuge, J. Udupa, P. Saha, Comput. Vis. Image Underst. 101, 177 (2006)
B. Carvalho, C. Gau, G. Herman, Y. Kong, Pattern Anal. Appl. 2, 73 (1999)
G. Herman, B. Carvalho, IEEE Trans. Pattern Anal. Mach. Intell. 23, 460 (2001)
B. Carvalho, G. Herman, Y. Kong, Discrete Appl. Math. 151, 65 (2005)
A. Pednekar, I. Kakadiaris, IEEE Trans. Image Process. 15(6), 1555 (2006)
X. Fan, J. Yang, L. Cheng, Lect. Notes Comput. Sci. 3613, 505 (2005)
Y. Boykov, O. Veksler, R. Zabih, IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1222 (2001)
Y. Boykov, M. Jolly, Proc. ICCV I, 105 (2001)
Y. Boykov, V. Kolmogorov, Proc. ICCV I, 26 (2003)
Y. Boykov, V. Kolmogorov, IEEE Trans. Pattern Anal. Mach. Intell. 26, 1124 (2004)
Y. Boykov, G. Funka-Lea, Int. J. Comput. Vis. 70, 109 (2006)
Y. Boykov, V. Kolmogorov, D. Cremers, A. Delong, Lect. Notes Comput. Sci. 3953, 409 (2006)
Y. Boykov, O. Veksler, in Handbook of Mathematical Models and Computer Vision (Springer, Berlin, 2006), chap. Graph cuts in vision and graphics: theories and applications, pp. 79–96
J. Shi, J. Malik, IEEE Trans. Pattern Anal. Mach. Intell. 22, 888 (2000)
P. Miranda, A. Falcao, J. Math. Imaging Vis. 35, 128 (2009)
S. Beucher, in Proceedings of the 10th Pfefferkorn Conference on Signal and Image Processing in Microscopy and Microanalysis, pp. 299–314 (1992)
L. Shafarenko, M. Petrou, J. Kittler, IEEE Trans. Image Process. 6, 1530 (1997)
J. Park, J. Keller, IEEE Trans. Pattern Anal. Mach. Intell. 23, 1201 (2001)
R. Malladi, J. Sethian, B. Vemuri, IEEE Trans. Pattern Anal. Mach. Intell. 17, 158 (1995)
J. Sethian, Fast Marching Methods and Level Sets Methods. Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge University Press, Cambridge, 1999)
P. Saha, J. Udupa, D. Odhner, Comput. Vis. Image Underst. 77, 145 (2000)
A. Falcao, J. Stolp, R. Lotufo, IEEE Trans. Pattern Anal. Mach. Intell. 26(1), 19 (2004)
K. Ciesielski, J. Udupa, Comput. Vis. Image Underst. 114, 155 (2010)
P.K. Saha, Comput. Vis. Image Underst. 99, 384 (2005)
K. Ciesielski, Set Theory for the Working Mathematician. No. 39 in London Mathematical Society Students Texts (Cambridge University Press, Cambridge, 1997)
K. Ciesielski, J. Udupa, Comput. Vis. Image Underst. 114, 146 (2010)
A. Rosenfeld, Inf. Control 40, 76 (1979)
A. Rosenfeld, Pattern Recognit. 16, 47 (1983)
A. Rosenfeld, Pattern Recognit. Lett. 2, 311 (1984)
V. Kolmogorov, R. Zabih, IEEE Trans. Pattern Anal. Mach. Intell. 26(2), 147 (2004)
R. Audigier, R. Lotufo, in Proceeding of the 19th Brazilian Symposium on Computer Graphics and Image Processing (2006)
M. Kass, A. Witkin, D. Terzopoulos, Int. J. Comput. Vis. 1, 321 (1987)
D. Mumford, J. Shah, Commun. Pure Appl. Math. 42, 577 (1989)
T. Chan, L. Vese, IEEE Trans. Image Process. 10, 266 (2001)
K. Ciesielski, J. Udupa, Proc. SPIE 6512 (2007)
J. Udupa, P. Saha, Proc. IEEE 91, 1649 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ciesielski, K.C., Udupa, J.K. (2010). Region-Based Segmentation: Fuzzy Connectedness, Graph Cut and Related Algorithms. In: Deserno, T. (eds) Biomedical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15816-2_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-15816-2_10
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15815-5
Online ISBN: 978-3-642-15816-2
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)