Unsupervised Clustering Method with Optimal Estimation of the Number of Clusters: Application to Image Segmentation

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http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.905473

15th International Conference on Patt ...

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	C. Rosenberger, K. Chehdi, "Unsupervised Clustering Method with Optimal Estimation of the Number of Clusters: Application to Image Segmentation," Pattern Recognition, International Conference on, vol. 1, pp. 1656, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 1, 2000.

	BibTex	x
	@article{ 10.1109/ICPR.2000.905473, author = {C. Rosenberger and K. Chehdi}, title = {Unsupervised Clustering Method with Optimal Estimation of the Number of Clusters: Application to Image Segmentation}, journal ={Pattern Recognition, International Conference on}, volume = {1}, year = {2000}, isbn = {0-7695-0750-6}, pages = {1656}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.905473}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - Unsupervised Clustering Method with Optimal Estimation of the Number of Clusters: Application to Image Segmentation SN - 0-7695-0750-6 SP EP A1 - C. Rosenberger, A1 - K. Chehdi, PY - 2000 VL - 1 JA - Pattern Recognition, International Conference on ER -

C. Rosenberger, ENSSAT-LASTI

K. Chehdi, ENSSAT-LASTI

We propose in this communication an unsupervised clustering method called MLBG based upon the K-means algorithm. The originality of this method lies in the automatic determination of the number of clusters by calling into question an intermediate result. This method also enables to improve the different steps in the K-means algorithm. We show the efficiency of the MLBG method through some experimental results and we demonstrate the usefulness of the technique for image segmentation.

Citation:

C. Rosenberger, K. Chehdi, "Unsupervised Clustering Method with Optimal Estimation of the Number of Clusters: Application to Image Segmentation," icpr, vol. 1, pp.1656, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 1, 2000

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