Gaussian mixture density modeling, decomposition, and applications

IEEE Transactions on Image Processing

Volumn 5, Issue 9, 1996, Pages 1293-1302

  Zhuang, Xinhua ^a,b   Huang, Yan ^b   Palaniappan, K ^a,c   Zhao, Yunxin ^a,d  

^a IEEE

^b University of Missouri   (United States)

^c UNIVERSITIES SPACE RESEARCH ASSOCIATION   (United States)

^d UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS;

CLUSTER EXTRACTION; GAUSSIAN DISTRIBUTION; GAUSSIAN MIXTURE DENSITY DECOMPOSITION; GAUSSIAN MIXTURE DENSITY MODELING;

IMAGE PROCESSING;

EID: 0030242069     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/83.535841     Document Type: Article

References (21)

1. G. R. Dattatreya and L. N. Kanal, "Estimation of mixing probabilities in multiclass finite mixtures," IEEE Trans. Syst., Man, Cybern., vol. 20, no. 1, pp. 149-158, 1990.
2. H. Derin, "Estimating components of univariate Gaussian mixtures using Prony's method," IEEE Trans. Pattern Anal. Machine Intell., vol. 9, no. 1, pp. 142-148, 1987.
3. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis. New York: Wiley, 1973.
4. K. Fukunaga, Statistical Pattern Recognition, 2nd ed. New York: Academic, 1990.
5. F. R. Hampel, E. M. Ronchetti, P.J. Rousseeuw, and W.A. Stahel, Robust Statistics: The Approach Based on Influence Functions. New York: Wiley, 1986.
6. P. J. Huber, Robust Statistics. New York: Wiley, 1981.
7. A. K. Jain and R. C. Dubes, Algorithms for Clustering Data. Englewood Cliffs, NJ: Prentice-Hall, 1988.
8. J. M. Jolion, P. Meer, and S. Bataouche, "Robust clustering with applications in computer vision," IEEE Trans. Pattern Anal. Machine Intell., vol. 13, no. 8, pp. 791-802, 1991.
9. J. N. Kapur, Maximum-Entropy Models in Science and Engineering. New York: Wiley, 1989.
10. J. S. Lee et al., "A processing strategy for automated pap smear screening," Analyt. Quan. Cytol. Histol., vol. 14, no. 5, Oct., 1992.
11. K. Palaniappan, "Multiresolution, adaptive methods, and classification for image analysis of dna autoradiographs," Ph.D. dissertation, Dept. Electr. Comput. Eng., Univ. Illinois, Urbana-Champaign, IL, 1991.
12. R. A. Redner and H. F. Walker, "Mixture densities, maximum likelihood and the EM algorithm," SIAM Rev., vol. 26, no. 2, pp. 195-239, 1984.
13. P. J. Rousseeuw and A. M. Leroy, Robust Regression and Outlier Detection. New York: Wiley, 1987.
14. R. Y. Rubinstein, Monte Carlo Optimization, Simulation and Sensitivity of Queuing Networks. New York: Wiley, 1986.
15. D. M. Titterington, A. F. M. Smith, and U. E. Markov, Statistical Analysis of Finite Mixture Distributions. New York: Wiley, 1985.
16. J. T. Tou and R. C. Gonzalez, Pattern Recognition Principles. Reading, MA: Addison-Wesley, 1974.
17. X. Zhuang and R. M. Haralick, "A highly robust estimator for computer vision," in Proc. 10th Int. Conf. Pattern Recog., Atlantic City, NJ, vol. 1, June 1990, pp. 545-550.
18. X. Zhuang, T. Wang, and P. Zhang, "A highly robust estimator through partially likelihood function modeling and its application in computer vision," IEEE Trans. Pattern Anal. Machine Intell., vol. 14, no. 1, pp. 19-35, 1992.
19. X. Zhuang, J. S. Lee, Y. Huang, and A. Nelson, "Staining independent Bayes classifier for automated cell pattern recognition," in Proc. IS&T/SPIE Symp. Electron. Imaging: Sci. Tech., San Jose, CA, 1993.
20. X. Zhuang and Y. Huang, "Robust 3D-3D pose estimation," in Proc. 4th Int. Conf. Comput. Vision, Berlin, Germany, 1993, pp. 567-571;
21. also in IEEE Trans. Pattern Anal. Machine Intell., vol. 16, no. 8, pp. 818-824, 1994.