An automatic shape independent clustering technique

Pattern Recognition

Volumn 37, Issue 1, 2004, Pages 33-45

  Bandyopadhyay, Sanghamitra ^a  

^a INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Graph partitioning; Hierarchical clusters; Non convex clusters; Relative neighborhood; Unsupervised pattern classification; Variable number of clusters

Indexed keywords

DATA REDUCTION; GRAPH THEORY;

SHAPE INDEPENDENT CLUSTERING;

PATTERN RECOGNITION;

SHAPE ANALYSIS;

EID: 0242573770     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(03)00235-8     Document Type: Article

References (17)

1. Anderberg M.R. Cluster Analysis for Application 1973 Academic Press New York
2. Duda R.O. Hart P.E. Pattern Classification and Scene Analysis 1973 Wiley New York
3. Tou J.T. Gonzalez R.C. Pattern Recognition Principles 1974 Addison-Wesley Reading, MA
4. Everitt B.S. Cluster Analysis 3rd Edition 1993 Edward Arnold London
5. Jain A.K. Dubes R.C. Algorithms for Clustering Data 1988 Prentice-Hall Englewood Cliffs, NJ
6. K. Alsabti, S. Ranka, V. Singh, An efficient k-means clustering algorithm, in: IPPS: 11th International Parallel Processing Symposium, IEEE Computer Society Press, Silver Spring, MD, 1998.
7. E. Hartuv, R. Shamir, A clustering algorithm based on graph connectivity, Inf. Process. Lett. (2000) 175-181.
8. Hansen P. Mladenovic N. J-Means: A new local search heuristic for minimum sum of squares clustering Pattern Recognition 34 2001 405-413
9. Wong C. Chen C. Su M. A novel algorithm for data clustering Pattern Recognition 34 2001 425-442
10. P.S. Bradley, U.M. Fayyad, C. Reina, Scaling clustering algorithms to large databases, in: Fourth International Conference on Knowledge Discovery and Data Mining, August 1998, New York City, USA, AAAI Press, pp. 9-15.
11. T. Zhang, R. Ramakrishnan, M. Livny, BIRCH: An efficient data clustering method for very large databases, in: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, Montreal, Canada, 1996, pp. 103-114.
12. Zahn C. Graph-theoretical methods for detecting and describing gestalt clusters IEEE Trans. Comput. C-20 1972 68-86
13. Theodoridis S. Koutroumbas K. Pattern Recognition 1999 Academic Press New York
14. Toussaint G.T. The relative neighborhood graph of a finite planar set Pattern Recognition 12 1980 261-268
15. Urquhart R. Graph theoretical clustering based on limited neighborhood sets Pattern Recognition 15 1982 173-187
16. Osbourn G.C. Martinez R.F. Empirically defined regions of influence for cluster analysis Pattern Recognition 28 1995 1793-1806
17. Bensaid A.M. Hall L.O. Bezdek J.C. Clarke L.P. Silbiger M.L. Arrington J.A. Murtagh R.F. Validity guided (re)clustering with applications to image segmentation IEEE Trans. Fuzzy Syst. 4 1996 112-123