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2009 Seventh International Conference on Advances in Pattern Recognition
Unsupervised Satellite Image Segmentation by Combining SA Based Fuzzy Clustering with Support Vector Machine
February 04-February 06
ISBN: 978-0-7695-3520-3
ASCII Text
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Anirban Mukhopadhyay, Ujjwal Maulik, "Unsupervised Satellite Image Segmentation by Combining SA Based Fuzzy Clustering with Support Vector Machine," Advances in Pattern Recognition, International Conference on, pp. 381-384, 2009 Seventh International Conference on Advances in Pattern Recognition, 2009.
 
 
BibTex
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@article{ 10.1109/ICAPR.2009.50,
author = {Anirban Mukhopadhyay and Ujjwal Maulik},
title = {Unsupervised Satellite Image Segmentation by Combining SA Based Fuzzy Clustering with Support Vector Machine},
journal ={Advances in Pattern Recognition, International Conference on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3520-3},
pages = {381-384},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICAPR.2009.50},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Advances in Pattern Recognition, International Conference on
TI - Unsupervised Satellite Image Segmentation by Combining SA Based Fuzzy Clustering with Support Vector Machine
SN - 978-0-7695-3520-3
SP381
EP384
A1 - Anirban Mukhopadhyay,
A1 - Ujjwal Maulik,
PY - 2009
KW - Fuzzy clustering
KW - simulated annealing
KW - support vector machine
KW - remote sensing images
VL - 0
JA - Advances in Pattern Recognition, International Conference on
ER -
 
Fuzzy clustering is an important tool for unsupervised pixel classification in remotely sensed satellite images. In this article, a Simulated Annealing (SA) based fuzzy clustering method is developed and combined with popular Support vector Machine (SVM) classifier to fine tune the clustering produced by SA for obtaining an improved clustering performance. The performance of the proposed technique has been compared with that of some other well-known algorithms for an IRS satellite image of the city of Kolkata and its superiority has been demonstrated quantitatively and visually.
Index Terms:
Fuzzy clustering, simulated annealing, support vector machine, remote sensing images
Citation:
Anirban Mukhopadhyay, Ujjwal Maulik, "Unsupervised Satellite Image Segmentation by Combining SA Based Fuzzy Clustering with Support Vector Machine," icapr, pp.381-384, 2009 Seventh International Conference on Advances in Pattern Recognition, 2009
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