Region merging using homogeneity and edge integrity for watershed-based image segmentation

Optical Engineering

Volumn 44, Issue 1, 2005, Pages 1-14

  Hernandez, Sergio E ^a   Barner, Kenneth E ^a   Yuan, Yu ^a  

^a UNIVERSITY OF DELAWARE   (United States)

Author keywords

Edge integrity; Image analysis; Image segmentation; Region homogeneity

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; IMAGE ANALYSIS; ITERATIVE METHODS; NONLINEAR FILTERING;

EDGE INTEGRITY; GRADIENT MAGNITUDE IMAGE; REGION HOMOGENEITY; WATERSHED BASED IMAGE SEGMENTATION;

IMAGE SEGMENTATION;

EID: 14544277946     PISSN: 00913286     EISSN: None     Source Type: Journal    
DOI: 10.1117/1.1830042     Document Type: Article

References (31)

1. N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern Recogn. 26(9), 1277-1294 (1993).
2. R. M. Haralick and L. G. Shapiro, "Image segmentation techniques," Comput. Vis. Graph. Image Process. 29, 100-132 (1985).
3. G. Iannizzotto and L. Vita, "Fast and accurate edge-based segmentation with no contour smoothing in 2-d real images," IEEE Trans. Image Process. 9, 1232-1237 (2000).
4. S. Beucher and F. Meyer, "The morphological approach tosegmentation: the watershed transformation," in Mathematical Morphology in Image Processing, E. R. Dougherty, Ed., pp. 433-481, Rochester, NY: Marcel Dekker (1993).
5. L. Vincent and P. Soille, "Watersheds in digital spaces: an efficient algorithm based on immersion simulations," IEEE Trans. Pattern Anal. Mach. Intell. 13, 583-598 (1991).
6. K. Haris, S. Efstratiadis, N. Maglaveras, and A. Katsaggelos, "Hybrid image segmentation using watersheds and fast region merging "IEEE Trans. Image Process. 7(12), 1684-1699 (1998).
7. J. M. Gauch, "Image segmentation and analysis via multiscale gradient watershed hierarchies," IEEE Trans. Image Process. 8(1), 69-79 (1999).
8. A. Bleau and L. J. Leon, "Watershed-based segmentation and region merging," Comput. Vis. Image Underst. 77, 317-370 (2000).
9. N. Malpica, J. E. Ortuno, and A. Santos, "A multichannel watershed-based algorithm for supervised texture segmentation," Pattern Recogn. Lett. 24, 1545-1554 (2003).
10. P. Moreels and S. E. Smrekar, "Watershed identification of polygonal patterns in noisy SAR images," IEEE Trans. Image Process. 12 740-750 (2003).
11. J. B. Roerdink and A. Meijster, "Watershed transform: definitions, aigorithms and parallelization strategies," Fundam. Inf. 41 187-228 (2000).
12. D. Wang, "A multiscale gradient algorithm for image segmentation using watersheds," Pattern Recogn. 30, 2043-2052 (1997).
13. D. H. Ballard and C. M. Brown, Eds., Computer Vision, Prentice-Hall, Englewood Cliffs, NJ (1982).
14. J. M. Beaulieu and M. Goldberg, "Hierarchy in picture segmentation: a stepwise optimization approach," IEEE Trans. Pattern Anal. Mach. Intell. 11, 150-163 (1989).
15. A. K. Jain, Ed., Fundamentals of Digital Image Processing, Prentice-Hall, Englewood Cliffs, NJ (1989).
16. D. Wang and C. Labit, "Morphological spatio-temporal simplification for video image segmentation," Signal Process. Image Commun. 11 161-170 (1997).
17. S. Chen, W. Lin, and C. Chen, "Split-and-merge image segmentation based on localized feature analysis and statistical tests," CVGIP Graph. Models Image Frocess. 53, 457-475 (1991).
18. L. E. Band, "Topographic partition of watersheds with digital elevation models," Water Resour. Res. 22(1), 15-24 (1986).
19. T. K. Puecker and D. H. Douglas, "Detection of surface-specific points by local parallel processing of discrete terrain elevation data," Comput. Vis. Graph. Image Process. 4, 375-387 (1975).
20. D. Marks, J. Dozier, and J. Frew, "Automated basin delineation from digital elevation data," Geoprocessing 2, 299-311 (1984).
21. S. H. Collins, "Terrain parameters directly from a digital terrain model," Can. Surveyor 29(5), 507-518 (1975).
22. H. Digabel and C. Lantuéjoul, "Iterative algorithms," in Proc. 2nd Eur. Symp. of Quantitative Analysis of Microstructures in Material Science, Biology and Medicine, J. L. Chermant, Ed., pp. 85-99, Stuttgart, Germany: Riederer Verlag (1978).
23. S. Beucher, "Watersheds of functions and picture segmentation," in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, pp. 1928-1931 (1982).
24. I. Sobel, Ed., "Camera models and machine perception," Stanford AI MEMO 121, Stanford University (1970).
25. O. Yli-Harja, J. Astola, and Y. Neuvo, "Analysis of the properties of median and weighted median filters using threshold logic and stack filter representation," IEEE Trans. Signal Process. 39(2), 395-409 (1991).
26. D. H. Yom and S. Ann, "Directed graph representation for root-signal set of median filters," Proc. IEEE 75, 1542-1544 (1987).
27. G. R. Arce, N. C. Gallagher, Jr., and T. A. Nodes, "Median filters: theory and applications," in Advances in Computer Vision and Image Processing, T. S. Huang, Ed., vol. 2, JAI Press (1986).
28. J. P. Fitch, E. J. Coyle, and N. C. Gallagher, Jr., "Median filtering by threshold decomposition," IEEE Trans. Acoust., Speech, Signal Process. 32, 1183-1188 (1984).
29. N. C. Gallagher, Jr. and G. L. Wise, "A theoreticai analysis of the properties of median filters," IEEE Trans. Acoust., Speech, Signal Process. 29, 1136-1141 (1981).
30. S. G. Tyan, "Median-filtering: deterministic properties," in Two-Dimensional Digital Signal Processing, II: Transforms and Median Filters, T. S. Huang, Ed., Chap. 5, pp. 197-217, Springer-Verlag, New York (1981).
31. D. Cortez, P. Nunes, M. M. de Sequeira, and F. Pereira, "Image segmentation towards new image representation methods," Signal Process. Image Commun. 6, 485-498 (1995).