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Volumn 29, Issue 9, 2008, Pages 1261-1273

Effective clustering and boundary detection algorithm based on Delaunay triangulation

Author keywords

Clustering algorithms; Data mining; Delaunay triangulation

Indexed keywords

COMPUTER GRAPHICS; DATA MINING; DATA PROCESSING; FEATURE EXTRACTION; MATHEMATICAL MODELS; STATISTICAL METHODS;

EID: 43249120533     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.01.028     Document Type: Article
Times cited : (52)

References (34)
  • 1
    • 6344252945 scopus 로고    scopus 로고
    • Adamson, A., Alexa, M., 2004. Approximating bounded, non-orientable surfaces from points. In: Proc. Shape Modeling International 2004, pp. 243-252.
    • Adamson, A., Alexa, M., 2004. Approximating bounded, non-orientable surfaces from points. In: Proc. Shape Modeling International 2004, pp. 243-252.
  • 2
    • 43249123249 scopus 로고    scopus 로고
    • Andersson, M., Giesen, J., Pauly, M., Speckmann, B., 2004. Bounds on the k-neighborhood for locally uniformly sampled surfaces. In: Proc. 1st Symposium on Point-Based Graphics, pp. 167-171.
    • Andersson, M., Giesen, J., Pauly, M., Speckmann, B., 2004. Bounds on the k-neighborhood for locally uniformly sampled surfaces. In: Proc. 1st Symposium on Point-Based Graphics, pp. 167-171.
  • 3
    • 0347172110 scopus 로고    scopus 로고
    • Ankerst, M., Breunig, Markus M., Kriegel, H.-P., Sander, J., 1999. OPTICS: Ordering points to identify the clustering structure. In: Proc. ACM SIGMOD Internat. Conf. on Management of Data SIGMOD'99, pp. 49-60.
    • Ankerst, M., Breunig, Markus M., Kriegel, H.-P., Sander, J., 1999. OPTICS: Ordering points to identify the clustering structure. In: Proc. ACM SIGMOD Internat. Conf. on Management of Data SIGMOD'99, pp. 49-60.
  • 5
    • 43249120922 scopus 로고    scopus 로고
    • Berkhin, Pavel, 2002. Survey of Clustering Data Mining Techniques. Tech. Rep., Accrue Software, San Jose, CA.
    • Berkhin, Pavel, 2002. Survey of Clustering Data Mining Techniques. Tech. Rep., Accrue Software, San Jose, CA.
  • 6
    • 0019563894 scopus 로고
    • Computing Dirichlet Tessellations
    • Bowyer A. Computing Dirichlet Tessellations. Comput. J. 24 (1981) 162-166
    • (1981) Comput. J. , vol.24 , pp. 162-166
    • Bowyer, A.1
  • 7
    • 43249122725 scopus 로고    scopus 로고
    • Eldershaw, C., Hegland, M., 1997. Cluster Analysis using Triangulation. In Proc. Computational Techniques and Applications: CTAC97, Singapore, pp. 201-208.
    • Eldershaw, C., Hegland, M., 1997. Cluster Analysis using Triangulation. In Proc. Computational Techniques and Applications: CTAC97, Singapore, pp. 201-208.
  • 8
    • 43249089642 scopus 로고    scopus 로고
    • Ester, M., Kriegel, H.-P., Sander, J., Xu, X., 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proc. 2nd Internat. Conf. on Knowledge Discovery and Data Mining, pp. 226-231.
    • Ester, M., Kriegel, H.-P., Sander, J., Xu, X., 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proc. 2nd Internat. Conf. on Knowledge Discovery and Data Mining, pp. 226-231.
  • 9
    • 43249129697 scopus 로고    scopus 로고
    • Estivill-Castro, V., Lee, I., 2000. AMOEBA: Hierarchical clustering based on spatial proximity using Delaunay diagram. In Proc. 9th Internat. Symposium on Spatial Data Handling, pp. 7a.26-7a.41.
    • Estivill-Castro, V., Lee, I., 2000. AMOEBA: Hierarchical clustering based on spatial proximity using Delaunay diagram. In Proc. 9th Internat. Symposium on Spatial Data Handling, pp. 7a.26-7a.41.
  • 10
    • 43249123795 scopus 로고    scopus 로고
    • Estivill-Castro, V., Lee, I., 2000. AUTOCLUST: Automatic clustering via boundary extraction for mining massive point-data sets. In: Proc. 5th Internat. Conf. on Geocomputation.
    • Estivill-Castro, V., Lee, I., 2000. AUTOCLUST: Automatic clustering via boundary extraction for mining massive point-data sets. In: Proc. 5th Internat. Conf. on Geocomputation.
  • 12
    • 43249106055 scopus 로고    scopus 로고
    • Fraley, C., Raftery, A.E., 2002. MCLUST: Software for model-based clustering, density estimation and discriminant analysis. Tech. Rep. 415. Department of Statistics, University of Washington.
    • Fraley, C., Raftery, A.E., 2002. MCLUST: Software for model-based clustering, density estimation and discriminant analysis. Tech. Rep. 415. Department of Statistics, University of Washington.
  • 13
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering, discriminant analysis, and density estimation
    • Fraley C., and Raftery A.E. Model-based clustering, discriminant analysis, and density estimation. J. Amer. Statist. Assoc. 97 (2002) 611-631
    • (2002) J. Amer. Statist. Assoc. , vol.97 , pp. 611-631
    • Fraley, C.1    Raftery, A.E.2
  • 14
    • 0026276861 scopus 로고
    • Problems with handling spatial data-the Voronoi approach
    • Gold C.M. Problems with handling spatial data-the Voronoi approach. CISM J. ACSGC 45 (1991) 65-80
    • (1991) CISM J. ACSGC , vol.45 , pp. 65-80
    • Gold, C.M.1
  • 16
    • 43249099602 scopus 로고    scopus 로고
    • Hader, S., Hamprecht, F.A., 2003. Efficient density clustering using basin spanning trees. In: Proc. 26th Annual Conf. of the Gesellschaft für Klassifikation (GfK1), pp. 39-48.
    • Hader, S., Hamprecht, F.A., 2003. Efficient density clustering using basin spanning trees. In: Proc. 26th Annual Conf. of the Gesellschaft für Klassifikation (GfK1), pp. 39-48.
  • 18
    • 43249083509 scopus 로고    scopus 로고
    • Hinneburg, A., Keim, D.A., 1998. An efficient approach to clustering in large multimedia databases with noise. In: Proc. 4th Internat. Conf. on Knowledge Discovery and Data Mining, pp. 58-65.
    • Hinneburg, A., Keim, D.A., 1998. An efficient approach to clustering in large multimedia databases with noise. In: Proc. 4th Internat. Conf. on Knowledge Discovery and Data Mining, pp. 58-65.
  • 21
    • 0025489075 scopus 로고
    • The self-organizing map
    • Kohonen T. The self-organizing map. Proc. IEEE 9 (1990) 1464-1479
    • (1990) Proc. IEEE , vol.9 , pp. 1464-1479
    • Kohonen, T.1
  • 22
    • 0000029675 scopus 로고
    • Two algorithms for constructing a Delaunay triangulation
    • Lee D.T., and Schacter B.J. Two algorithms for constructing a Delaunay triangulation. Internat. J. Comput. Inform Sci 3 (1980) 219-241
    • (1980) Internat. J. Comput. Inform Sci , vol.3 , pp. 219-241
    • Lee, D.T.1    Schacter, B.J.2
  • 23
    • 43249122194 scopus 로고    scopus 로고
    • MacQueen, J., 1967. Some methods for classification and analysis of multivariate observations. In: Proc. 5th Berkeley Symp. Math. Statist. Prob., pp. 281-297.
    • MacQueen, J., 1967. Some methods for classification and analysis of multivariate observations. In: Proc. 5th Berkeley Symp. Math. Statist. Prob., pp. 281-297.
  • 25
    • 0000743235 scopus 로고
    • State of the art in pattern recognition
    • Nagy G. State of the art in pattern recognition. Proc. IEEE 56 (1968) 836-863
    • (1968) Proc. IEEE , vol.56 , pp. 836-863
    • Nagy, G.1
  • 26
    • 43249113188 scopus 로고    scopus 로고
    • Ng, R.T., Han, J., 1994. Efficient and effective clustering methods for spatial data mining. In: Proc. 20th Internat. Conf. on Very Large Data Bases VLDB 94, Santiago, Chile, pp. 144-155.
    • Ng, R.T., Han, J., 1994. Efficient and effective clustering methods for spatial data mining. In: Proc. 20th Internat. Conf. on Very Large Data Bases VLDB 94, Santiago, Chile, pp. 144-155.
  • 28
    • 0036450357 scopus 로고    scopus 로고
    • Pauly, M., Gross, M., Kobbelt, L., 2002. Efficient simplification of point-sampled surfaces. In: Proc. Conf. on Visualization'02, pp. 163-170.
    • Pauly, M., Gross, M., Kobbelt, L., 2002. Efficient simplification of point-sampled surfaces. In: Proc. Conf. on Visualization'02, pp. 163-170.
  • 30
    • 0019563697 scopus 로고
    • Computing the n-dimensional Delaunay Tessellation with application to Voronoi Polytopes
    • Watson D.F. Computing the n-dimensional Delaunay Tessellation with application to Voronoi Polytopes. Comput. J. 24 (1981) 167-172
    • (1981) Comput. J. , vol.24 , pp. 167-172
    • Watson, D.F.1
  • 32
    • 0014976008 scopus 로고
    • Graph-theoretical methods for detecting and describing gestalt clusters
    • Zahn C.T. Graph-theoretical methods for detecting and describing gestalt clusters. IEEE Trans. Comput. 20 1 (1971) 68-86
    • (1971) IEEE Trans. Comput. , vol.20 , Issue.1 , pp. 68-86
    • Zahn, C.T.1
  • 33
    • 0036506135 scopus 로고    scopus 로고
    • Self-splitting competitive learning: A new online clustering paradigm
    • Zhang Y.J., and Liu Z.Q. Self-splitting competitive learning: A new online clustering paradigm. IEEE Trans. Neural Networks 13 (2002) 369-380
    • (2002) IEEE Trans. Neural Networks , vol.13 , pp. 369-380
    • Zhang, Y.J.1    Liu, Z.Q.2
  • 34
    • 0030157145 scopus 로고    scopus 로고
    • Zhang, T., Ramakrishnan, R., Livny, M., 1996. BIRCH: An efficient data clustering method for very large databases. In: Proc. 1996 ACM SIGMOD Internat. Conf. on Management of data, pp. 103-114.
    • Zhang, T., Ramakrishnan, R., Livny, M., 1996. BIRCH: An efficient data clustering method for very large databases. In: Proc. 1996 ACM SIGMOD Internat. Conf. on Management of data, pp. 103-114.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.