Image segmentation based on multiresolution Markov random field with fuzzy constraint in wavelet domain

IET Image Processing

Volumn 6, Issue 3, 2012, Pages 213-221

  Zheng, C ^a   Qin, Q ^a   Liu, G ^b   Hu, Y ^a  

^a WUHAN UNIVERSITY   (China)

^b ANYANG NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY FIELDS; FUZZY METHODS; FUZZY-CONSTRAINT; MARKOV RANDOM FIELD MODEL; MARKOV RANDOM FIELDS; MULTI-RESOLUTIONS; NATURAL IMAGES; NEW MODEL; SPATIAL CONSTRAINTS; SUBFIELDS; WAVELET DOMAIN;

IMAGE PROCESSING; SIGNAL PROCESSING;

IMAGE SEGMENTATION;

EID: 84859083574     PISSN: 17519659     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-ipr.2010.0176     Document Type: Article

References (24)

1. Lee, H.K., and Kim, J.H.: 'An HMM-based threshold model approach for gesture recognition', IEEE Trans. Pattern Anal. Mach. Intell., 1999, 21, (10), p. 961-97310.1109/34.799904 0162-8828
2. Losada, C., Mazo, M., Palazuelos, S., and Redondo, F.: 'Adaptive threshold for robust segmentation of mobile robots from visual information of their own movement', Wisp 2009: Proc. Sixth IEEE Int. Symp. on Intelligent Signal Processing, 2009, p. 293-298
3. Malpica, N., deSolorzano, C.O., and Vaquero, J.J.: et al. 'Applying watershed algorithms to the segmentation of clustered nuclei', Cytometry, 1997, 28, (4), p. 289-29710.1002/(SICI)1097-0320(19970801)28:4<289::AID-CYTO3>3.0.CO;2-7
4. Grau, V., Mewes, A.U.J., Alcaniz, M., Kikinis, R., and Warfield, S.K.: 'Improved watershed transform for medical image segmentation using prior information', IEEE Trans. Med. Imaging, 2004, 23, (4), p. 447-45810.1109/TMI.2004.824224 0278-0062
5. Comaniciu, D., and Meer, P.: 'Mean shift: a robust approach toward feature space analysis', IEEE Trans. Pattern Anal. Mach. Intell., 2002, 24, (5), p. 603-61910.1109/34.1000236 0162-8828
6. Fei, W., and Zhu, S.: 'Mean shift clustering-based moving object segmentation in the H.264 compressed domain', IET Image Process., 2222, 4, (1), p. 11-1810.1049/iet-ipr.2009.0038
7. Dosselmann, R., and Yang, X.D.: 'Mean shift particle-based texture granularity', IEEE Instrumentation and Measurement Technology Conf., 2008, 1-5, p. 101-106
8. Geman, S., and Geman, D.: 'Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images', IEEE Trans. Pattern Anal. Mach. Intell., 1984, PAMI-6, (6), p. 721-74110.1109/TPAMI.1984.4767596 0162-8828
9. Besag, J.: 'On the statistical analysis of dirty pictures', J. R. Stat. Soc., 1986, 48, p. 259-30210.1080/02664769300000059
10. Krishnamachari, S., and Chellappa, R.: 'Multiresolution Gauss-Markov random field models for texture segmentation', IEEE Trans. Image Process., 1997, 6, (2), p. 251-26710.1109/83.551696 1057-7149
11. Comer, M.L., and Delp, E.J.: 'Segmentation of textured images using a multiresolution Gaussian autoregressive model', IEEE Trans. Image Process., 1999, 8, (3), p. 408-42010.1109/83.748895 1057-7149
12. Noda, H., Shirazi, M.N., and Kawaguchi, E.: 'MRF-based texture segmentation using wavelet decomposed images', Pattern Recognit., 2002, 35, (4), p. 771-78210.1016/S0031-3203(01)00077-2 0031-3203
13. Gui-Song, X., Chu, H., and Hong, S.: 'An unsupervised segmentation method using Markov random field on region adjacency graph for SAR images', Int. Conf. on Radar, CIE'06, 2006, October 16-19 2006, p. 1-4
14. Liu, G., Mao, L., Wang, L., and Qin, Q.: 'Texture segmentation based in a hierarchical Markov model in wavelet domain', Geomatics Inf. Sci. Wuhan Univ., 2009, 34, (5), p. 531-534
15. Scarpa, G., Gaetano, R., Haindl, M., and Zerubia, J.: 'Hierarchical multiple Markov chain model for unsupervised texture segmentation', IEEE Trans. Image Process., 2009, 18, (8), p. 1830-184310.1109/TIP.2009.2020534 1057-7149
16. Bouman, C., and Liu, B.: 'Multiple resolution segmentation of textured images', IEEE Trans. Pattern Anal. Mach. Intell., 1991, 13, (2), p. 99-11310.1109/34.67641 0162-8828
17. Liang, K.-H., and Tjahjadi, T.: 'Adaptive scale fixing for multiscale texture segmentation', IEEE Trans. Image Process., 2006, 15, (1), p. 249-25610.1109/TIP.2005.860340 1057-7149
18. Hammersley, J., and Clifford, P.: 'Markov field on finite graphs and lattices', Unpublished
19. Derin, H., and Elliott, H.: 'Modeling and segmentation of noisy and textured images using Gibbs random fields', IEEE Trans. Pattern Anal. Mach. Intell., 1987, PAMI-9, (1), p. 39-5510.1109/TPAMI.1987.4767871 0162-8828
20. Dempster, A.P., Laird, N.M., and Rubin, D.B.: 'Maximum likelihood from incomplete data via the EM algorithm', J. R. Stat. Soc., B., 1977, 39, (1), p. 1-38
21. Available from: http://www.ux.uis.no/~tranden/brodatz.html, accessed 1966
22. Available from: http://mosaic.utia.cas.cz/, accessed 2008
23. Unnikrishnan, R., and Hebert, M.: 'Measures of similarity', Seventh IEEE Workshops Application of Computer Vision, WACV/MOTIONS '05, 2005, vol. 1, p. 394
24. http://www-i6.informatik.rwth-aachen.de/dagmdb/index.php/Content-Based_Image_Retrieval