loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
15th International Conference on Pattern Recognition (ICPR'00) - Volume 1
Unsupervised Clustering Method with Optimal Estimation of the Number of Clusters: Application to Image Segmentation
Barcelona, Spain
September 03-September 08
ISBN: 0-7695-0750-6
ASCII Text
x 
 
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
Usage of this product signifies your acceptance of the Terms of Use.