Color image segmentation using a self-initializing EM algorithm

Proceedings of the 6th IASTED International Conference on Visualization, Imaging, and Image Processing, VIIP 2006

Volumn , Issue , 2006, Pages 417-424

  Ilea, Dana Elena ^a   Whelan, Paul F ^a  

^a DUBLIN CITY UNIVERSITY   (Ireland)

Author keywords

Color segmentation; Diffusion filtering; EM; Initialization

Indexed keywords

ADAPTIVE ALGORITHMS; AGRICULTURAL PRODUCTS; ALGORITHMS; COLOR IMAGE PROCESSING; DIGITAL IMAGE STORAGE; IMAGE PROCESSING; IMAGE SEGMENTATION; IMAGING SYSTEMS; OPTICAL PROPERTIES; VISUALIZATION;

ADAPTIVE IMAGE SEGMENTATIONS; ALGORITHM PARTITIONS; COLOR IMAGE SEGMENTATIONS; COLOR IMAGES; COLOR SEGMENTATION; COLOR SEGMENTATIONS; DIFFUSION FILTERING; EFFECTIVE SOLUTIONS; EM; EM ALGORITHMS; EXPECTATION MAXIMIZATIONS; EXPERIMENTAL DATUMS; INITIALIZATION; INITIALIZATION STAGES;

COLOR;

EID: 56349148330     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. Y. Deng & B.S. Manjunath, Unsupervised segmentation of color-texture regions in images and video, IEEE Trans. Pattern Analysis Machine Intell,, 23(8), 2001, 800-810.
2. J. Mukherjee, MRF Clustering for segmentation of color images, Pattern Recognition Letters, 23(8), 2002, 917-929.
3. H.D. Cheng, X. Jiang, Y. Sun, & J. Wang, Colour image segmentation: advances and prospects, Pattern Recognition, 34(12), 2001, 2259-2281.
4. L. Shafarenko, M. Petrou, & J. Kittler, Histogram-based segmentation in a perceptually uniform color space, IEEE Trans. on Image Processing, 7(9), 1998, 1354-1358.
5. D. Comaniciu & P. Meer, Mean Shift. A robust approach toward feature space analysis, IEEE Trans. Pattern Analysis Machine Intell, 24(5), 2002, 603-619.
6. A. Diplaros, T. Gevers, & N. Vlassis, Skin detection using the EM algorithm with spatial constraints, IEEE International Conference on Systems, Man and Cybernetics, vol. 4, Hague, Netherlands, 2004, 3071-3075.
7. L. Hermes, T. Zöller, & J. M. Buhmann, Parametric distributional clustering for image segmentation, 7th European Conference on Computer Vision (ECCV), Copenhagen, Denmark, 2002, 577-591.
8. S. Lakshmanan & H. Derin, Simultaneous parameter estimation and segmentation of Gibbs Random Fields using simulated annealing, IEEE Trans. Pattern Analysis Machine Intell., 11(8), 1989, 799-813.
9. J.A. Bilmes, A Gentle Tutorial of the EM algorithm and its application to parameter estimation for Gaussian Mixed and Hidden Markov Models (U.C. Berkely, California, April 1998, TR-97-021).
10. P. McKenzie & M. Alder, Initializing the EM algorithm for use in Gaussian mixture modeling, In E.S. Gelsema and L.N. Kanal, Editors, Pattern Recognition in Practice IV, Elsevier, 1994, 91-105.
11. A.P. Dempster, N.M. Laird, & D.B. Rubin, Maximum likelihood estimation from incomplete data via the EM algorithm, Journal of the Royal Statistical Society (B), 39(1), 1977, 1-38.
12. J.M. Pena, J.A. Lozano, & P. Larranaga, An empirical comparison of four initialization methods for the K-Means algorithm, Pattern Recognition Letters, vol. 20(10), 1999, 1027-1040.
13. C. Biernacki, G. Celeux, & G. Govaert, Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models, Computational Statistics and Data Analysis, 41(3), 2003, 561-575.
14. S. Khan & A. Ahmad, Cluster centre initialisation algorithm for K-Means clustering, Pattern Recognition Letters, 25(11), 2004, 1293-1302.
15. M. Meila & D. Heckerman, An experimental comparison of several clustering methods (Microsoft Research Technical Report, 1998, MSR-TR-98-06).
16. M. Sonka, V. Hlavac, & R. Boyle, Image processing, analysis and machine vision (2nd edition, PWS Boston, 1998).
17. K. Tang, J. Astola, & Y. Neuovo, Nonlinear multivariate image filtering techniques, IEEE Trans. Image Processing, 4(6), 1995, 788-797.
18. P. Perona & J. Malik, Scale-space and edge detection using anisotropic diffusion, IEEE Trans. Pattern Analysis Machine Intell, 12(7), 1990, 629-639.
19. J. Weickert, Coherence-enhancing diffusion of colour images, Image and Vision Computing, 17(3), 1999, 201-212.
20. M. Black, G. Sapiro, D. Marimont, & D. Heeger, Robust anisotropic diffusion, IEEE Trans. Image Proc., 7(3), 1998, 421-432.
21. F.S. Hill, Computer graphics (Macmillan Publishing 1990).
22. X. Wu, Efficient statistical computations for optimal color quantization, Graphics Gems 2, Academic Press, 1991.
23. J. Puzicha, M. Held, J. Ketterer, J.M. Buhmann, & D. Fellner, On spatial quantization of color images. IEEE Trans. Image Processing, 9(4), 2000, 666-682.
24. P. Nammalwar, O. Ghita, & P.F. Whelan, Integration of feature distributions for colour texture segmentation, 17th International Conference on Pattern Recognition (ICPR 2004), vol. 1, 2004, 716 - 719.
25. T. Ojala, M. Pietikainen, & T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Trans. Pattern Analysis Machine Intell., 24(7), 2002, 971-987.
26. th Scandinavian Conference on Image Analysis, Joensuu, Finland, 2005, 892-900.