Seeded Region Growing

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 16, Issue 6, 1994, Pages 641-647

  Adams, Rolf ^a   Bischof, Leanne ^a  

^a CSIRO MATHEMATICAL AND INFORMATION SCIENCES   (Australia)

Author keywords

Image segmentation; region growing; semiinteractive image processing; watershed

Indexed keywords

ALGORITHMS; CURVE FITTING; DECISION THEORY; IMAGE ANALYSIS; INTERACTIVE COMPUTER SYSTEMS; PATTERN RECOGNITION; SEED; SET THEORY; USER INTERFACES; WATERSHEDS;

IMAGE COMPOSITION; IMAGE SEGMENTATION; MANUAL SEED SELECTION; POSTULATE; REGION GROWING; SEMIINTERACTIVE IMAGE PROCESSING; TUNING PARAMETERS;

IMAGE PROCESSING;

EID: 0028444401     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.295913     Document Type: Article

References (16)

1. R. Adams, “Two new methods for seeded or semi-interactive image processing,” Proc. APRS Conf. Digital Image Computing: Techniques Appl., 1991, pp. 459-465.
2. D. H. Ballard and C. M. Brown, Computer Vision. Englewood Cliffs, NJ: Prentice-Hall, 1982.
3. P. J. Besl and R. C. Jain, “Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-10, pp. 167-192, 1988.
4. F. Cheevasuvit, H. Maitre, and D. Vidal-Madjar, “A robust method for picture segmentation based on split-and-merge procedure,” Comput. Vis, Graph. image Process., vol. 34, pp. 268-281, 1986.
5. S-Y. Chen, W-C. Lin, and C-T. Chen, “Split-and-merge image segmentation based on localized feature analysis and statistical tests,” CVGIP: Graphic. Models Image Processing, vol. 53, no. 5, pp. 457-475, 1991.
6. L. S. Davis, “A survey of edge detection techniques,” Comput. Graph. Image Process., vol. 4, pp. 248-270, 1975.
7. D. Y. Hand, Discrimination and Classification. New York: Wiley, 1981.
8. R. M. Haralick and L. G. Shapiro, “Image segmentation techniques,” Comput. Vis. Graph. Image Process., vol. 29, pp. 100-132, 1985.
9. S. L. Horowitz and T. Pavlidis, “Picture segmentation by a directed split-and-merge procedure,” Proc. 2nd Int. Joint Conf. Pattern Recognit., 1974, pp. 424-433.
10. F. Meyer and S. Beucher, “Morphological segmentation,” J. Vis. Commun. mun. Image Represent., vol. 1, pp. 21-46, 1990.
11. L. O'Gorman and A. C. Sanderson, “The converging squares algorithm: An efficient method for locating peaks in multidimensions,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, pp. 280-288, 1984.
12. T. Pavlidis and Y-T. Liow, “Integrating region growing and edge detection,” IEEE Trans. Pattern Anal. Machine Intell., vol. 12, pp. 225-233, 1990.
13. P. K. Sahoo, S. Soltani, and A. K. C. Wong, “A survey of thresholding techniques,” Comput. Via., Graph. Image Process., vol. 41, pp. 233-260, 1988.
14. J. Serra, Image Analysis and Mathematical Morphology. New York: Academic Press, 1982, pp. 390-423.
15. L. Vincent and P. Soille, “Watersheds in digital spaces: An efficient algorithm based on immersion simulations,” IEEE Trans. Pattern Anal. Machine Intell., vol. 13, pp. 583-598, 1991.
16. S. W. Zucker, “Region growing: Childhood and adolescence,” Comput. Graph. Image Process., vol. 5, pp. 382-399, 1976.