Classification of multispectral images using support vector machines based on PSO and K-Means clustering

This paper focusses on classification of multispectral images based on hybrid clustering using SVM and ML classifiers. Hybrid clustering combines both PSO and K-means clustering. K-means clustering is done initially and the result is used to seed the initial swarm. Based on these clusters, classific...

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Bibliographic Details
Main Authors: Venkatalakshmi, K., Shalinie, S.M.
Format: Conference Proceeding
Language:English
Subjects:
Clustering algorithms
Educational institutions
Image classification
Logic
Multispectral imaging
Neural networks
Quadratic programming
Support vector machine classification
Support vector machines
Topology
Online Access:Request full text
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Summary:This paper focusses on classification of multispectral images based on hybrid clustering using SVM and ML classifiers. Hybrid clustering combines both PSO and K-means clustering. K-means clustering is done initially and the result is used to seed the initial swarm. Based on these clusters, classification is done using ML and SWM classifiers. The results of these individual classifiers are combined in the decision fusion centre using XNOR Boolean logic.
DOI:10.1109/ICISIP.2005.1529435