Weight adaptation and oscillatory correlation for image segmentation

IEEE Transactions on Neural Networks

Volumn 11, Issue 5, 2000, Pages 1106-1123

  Chen, Ke ^a,b   Wang, DeLiang ^a,c   Liu, Xiuwen ^c  

^a IEEE

^b PEKING UNIVERSITY   (China)

^c OHIO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CORRELATION METHODS; IMAGE QUALITY; IMAGE SEGMENTATION; ITERATIVE METHODS;

DESYNCHRONIZATION; FEATURE-PRESERVING SMOOTHING ALGORITHMS; OSCILLATORY CORRELATIONS;

NEURAL NETWORKS;

EID: 0034270235     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.870043     Document Type: Article

References (44)

1. R. Adams and L. Bischof, "Seeded region growing," IEEE Trans. Pattern Anal. Mach. Intell., vol. 16, pp. 641-647, 1994.
2. N. Ahuja, "A transform for multiscale image segmentation by integrated edge and region detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 18, pp. 1211-1235, 1996.
3. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford, U.K.: Oxford Univ. Press, 1995.
4. T. Caelli and W. Bischof, Machine Learning and Image Interpretation. New York: Plenum, 1997.
5. M. Cheriet, J. N. Said, and C. Y. Suen, "A recursive thresholding technique for image segmentation," IEEE Trans. Image Processing, vol. 7, pp. 918-921, 1998.
6. F. Crick, "Function of the thalamic reticular complex: The searchlight hypothesis," Proc. Nat. Acad. Sci. USA, vol. 81, pp. 4586-4590, 1984.
7. G. Foresti, V. Murino, C. S. Regazzoni, and G. Vernazza, "Group of rectilinear segments by labeled Hough transform," CVGIP: Image Understand., vol. 58, pp. 22-42, 1994.
8. S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-6, pp. 721-741, 1984.
9. D. Geman, S. Geman, C. Graffigne, and P. Dong, "Boundary detection by constrained optimization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, pp. 609-628, 1990.
10. E. M. Gurari and H. Wechsler, "On the difficulties involved in the segmentation of pictures," IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-4, pp. 304-306, 1982.
11. J. F. Haddon and J. F. Boyce, "Image segmentation by unifying region and boundary information," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, pp. 929-948, 1990.
12. R. M. Haralick, "Statistical and structural approaches to texture," Proc. IEEE, vol. 67, pp. 786-804, 1979.
13. R. M. Haralick and L. G. Shapiro, "Image segmentation techniques," Comput. Graph. Image Process., vol. 29, pp. 100-132, 1985.
14. R. M. Horowitz and T. Pavlidis, "Picture segmentation by a tree traversal algorithm," J. ACM, vol. 23, pp. 368-388, 1976.
15. J. Koenderink, "The structure of images," Biol. Cybern., vol. 50, pp. 363-370, 1984.
16. J. Koh, M. Suk, and S. M. Bhandarkar, "A multilayer self-organizing feature map for range image segmentation," Neural Networks, vol. 8, pp. 67-86, 1995.
17. R. Kohler, "A segmentation system based on thresholding," Comput. Graphics Image Process., vol. 15, pp. 319-338, 1981.
18. T. Kohonen, Self-Organizing Maps. New York: Springer-Verlag, 1995.
19. A. Lev, S. Zucker, and A. Rosenfeld, "Iterative enhancement of noisy images," IEEE Trans. Syst., Man, Cybern., vol. SMC-7, pp. 435-442, 1977.
20. S. P. Liou, A. H. Chiu, and R. C. Jain, "A parallel technique for signal-level perceptual organization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, pp. 317-325, 1991.
21. B. S. Manjunath and R. Chellappa, "A unified approach to boundary perception: Edges, textures, and illusory contours," IEEE Trans. Neural Networks, vol. 4, pp. 96-108, Jan. 1993.
22. R. Mohan and R. Nevatia, "Perceptual organization for scene segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 14, pp. 616-635, 1992.
23. N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern Recognit., vol. 26, pp. 1277-1294, 1993.
24. T. Pavlidis and Y. T. Liow, "Integrating region growing and edge detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, pp. 225-233, 1990.
25. P. Perona and J. Malik, "Scale-space and edge detection using anisotropic diffusion," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, pp. 629-639, 1990.
26. C. Revol and M. Jourlin, "A new minimum variance region growing algorithm for image segmentation," Pattern Recognit. Lett., vol. 18, pp. 249-258, 1997.
27. B. D. Ripley, Pattern Recognition and Neural Networks. Cambridge, MA: Cambodge Univ. Press, 1996.
28. P. Saint-Marc, J. S. Chen, and G. Medioni, "Adaptive smoothing: A general tool for early vision," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, pp. 514-529, 1991.
29. S. Sarkar and K. L. Boyer, "On optimal infinite impulse response edge detection filters," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, pp. 1154-1171, 1991.
30. _, "Integration, inference, and management of spatial information using Bayesian networks: Perceptual organization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 15, pp. 256-274, 1993.
31. R. J. Schalkoff, Digital Image Processing and Computer Vision. New York: Wiley, 1989.
32. N. Shareef, D. L. Wang, and R. Yagel, "Segmentation of medical images using LEGION," IEEE Trans. Med. Imag., vol. 18, pp. 74-91, 1999.
33. D. Terman and D. L. Wang, "Global competition and local cooperation in a network of neural oscillators," Physica D, vol. 81, pp. 148-176, 1995.
34. B. van der Pol, "On 'relaxation oscillations'," Philos. Mag., vol. 2, pp. 978-992, 1926.
35. C. von der Malsburg, "The Correlation theory of brain function," Max-Planck-Institut for Biophys. Chem., Göttingen, Germany, Internal Rep. 81-2, 1981.
36. C. von der Malsburg and W. Schneider, "A neural cocktail-part processor," Biol. Cybern., vol. 54, pp. 29-40, 1986.
37. D. L. Wang, "Emergent synchrony in locally coupled neural oscillators," IEEE Trans. Neural Networks, vol. 6, pp. 941-948, 1995.
38. D. L. Wang and D. Terman, "Locally excitatory globally inhibitory oscillator networks," IEEE Trans. Neural Networks, vol. 6, pp. 283-286, 1995.
39. _, "Image segmentation based on oscillatory correlation," Neural Computat., vol. 9, pp. 805-836, 1997. (for errata see Neural Computat., vol. 9, pp. 1623-1626, 1997).
40. J. Weickert, "Theoretical foundations of anisotropic diffusion in image processing," Computing, vol. 11, pp. 221-236, 1996.
41. _, "A review of nonlinear diffusion filtering," in Scale-Space Theory in Computer Vision, B. Romeny, L. Florack, J. Koenderink, and M. Viergever, Eds. New York: Springer-Verlag, 1997, pp. 3-28.
42. R. Wilson and M. Spann, Image Segmentation and Uncertainty. New York: Wiley, 1996.
43. S. C. Zhu and Y. Yuille, "Region competition: Unifying snakes, region growing, and Bayes/MDL for multiband image segmentation," IEEE Trans. Pattern Anal. Mach. Intell., vol. 18, pp. 884-900, 1996.
44. S. W. Zucker, "Region growing: Childhood and adolescence," Comput. Graph. Image Process., vol. 5, pp. 382-399, 1976.