DocumentCode :
2360895
Title :
Classification of multispectral images using support vector machines based on PSO and K-Means clustering
Author :
Venkatalakshmi, K. ; Shalinie, S. Mercy
Author_Institution :
Dept. of I.T., Thiagarajar Coll. of Eng., Madurai, India
fYear :
2005
fDate :
4-7 Jan. 2005
Firstpage :
127
Lastpage :
133
Abstract :
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.
Keywords :
image classification; pattern clustering; support vector machines; K-Means clustering; ML classifier; PSO clustering; XNOR Boolean logic; hybrid clustering; multispectral image classification; support vector machines; Clustering algorithms; Educational institutions; Image classification; Logic; Multispectral imaging; Neural networks; Quadratic programming; Support vector machine classification; Support vector machines; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Sensing and Information Processing, 2005. Proceedings of 2005 International Conference on
Print_ISBN :
0-7803-8840-2
Type :
conf
DOI :
10.1109/ICISIP.2005.1529435
Filename :
1529435
Link To Document :
بازگشت