• 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