A Markov random field model for mode detection in cluster analysis

Pattern Recognition Letters

Volumn 29, Issue 9, 2008, Pages 1197-1207

  Moussa, Ahmed ^a   Sbihi, Abderrahmane ^b   Postaire, Jack Gérard ^c  

^a ABDELMALEK ESSAADI UNIVERSITY   (Morocco)

^b IBN TOFAIL UNIVERSITY   (Morocco)

^c UNIV LILLE   (France)

Author keywords

Classification; Gibbs distribution; Markov field; Mode detection; Potential function

Indexed keywords

CLUSTER ANALYSIS; MATHEMATICAL MODELS; STATISTICAL METHODS; UNSUPERVISED LEARNING;

GIBBS DISTRIBUTION; MARKOV FIELDS; MODE DETECTION; POTENTIAL FUNCTIONS;

MARKOV PROCESSES;

EID: 43249110026     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.01.033     Document Type: Article

References (16)

1. Clifford P. Markov random fields in statistics. In: Grimmett G.R., and Welsh D.J.A. (Eds). Disorder in Physical Systems. A Volume in Honour of J.M. Hammersley (1990), Clarendon Press, Oxford
2. Cohen F.S., and Cooper D.B. Simple parallel hierarchical and relaxation algorithms for segmenting noncausal Markovian random fields. IEEE Trans. Pattern Anal. Machine Intell. 9 2 (1987) 195-219
3. Cornuet J.M., and Fresnaye J. Etude Biométrique de Colonies d'Abeilles d'Espagne et du Portugal. Apidology 20 (1989) 93-101
4. Duda R.O., Hart P.E., and Stork D.G. Pattern Classification. second ed. (2001), Wiley Interscience, New York
5. Fresnaye, J., 1985. Biométrie de l'Abeille. Technical Report. National Institute of Agricultural Research (INRA), France.
6. Geman S., and Geman D. Stochastic relaxation, Gibbs distribution and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intell. 6 (1984) 721-741
7. Hofmann T., and Buhmann J.M. Pairwise data clustering by deterministic annealing. IEEE Trans. Pattern Anal. Machine Intell. 19 1 (1997) 1-14
8. Jain A.K., and Dubes R.C. Algorithms for Clustering Data (1988), Prentice-Hall, Englewood Cliffs
9. Lakshmanan S., and Derin H. Simultaneous parameter estimation and segmentation of Gibbs random field using simulated annealing. IEEE Trans. Pattern Anal. Machine Intell. 11 (1989) 799-813
10. Postaire J.G., and Vasseur C.P.C. An approximate solution to normal mixture identification with application to unsupervised pattern classification. IEEE Trans. Pattern Anal. Machine Intell. 3 2 (1981) 163-179
11. Postaire J.G., Zhang R.D., and Botte-Lecocq C. Cluster analysis by binary morphology. IEEE. Trans. Pattern Anal. Machine Intell. 15 2 (1993) 170-180
12. Puzicha J., Hofmann T., and Buhmann J.M. A theory of proximity based clustering: Structure detection by optimisation. Pattern Recognition 33 4 (1999) 617-634
13. Ruttner F. Biogeography and Taxonomy of Honeybees (1988), Springer, Berlin pp. 228-237
14. Touzani A., and Postaire J.G. Mode detection by relaxation. IEEE Trans. Pattern Anal. Machine Intell. 10 6 (1988) 970-978
15. Touzani A., and Postaire J.G. Clustering by mode boundary detection. Pattern Recognition Lett. 9 1 (1989) 1-12
16. Zhang G.P. Neural networks for classification: A survey. IEEE Trans. Systems Man Cybernet. 30 4 (2000) 451-462