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Abstract

Here an efficient and novel approach was considered as a combination of PCA, LDA and support vector machine. This method consists of three steps: I) dimension reduction using PCA, ii) feature extraction using LDA, iii) classification using SVM. Combination of PCA and LDA is used for improving the capability of LDA when new samples of images are available and SVM is used to reduce misclassification caused by not linearly separable classes.

Keywords

Dimension Reduction Feature Extraction Classification Support Vector Machine 

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Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • U. Raghavendra
    • 1
  • P. K. Mahesh
    • 2
  • Anjan Gudigar
    • 2
  1. 1.Manipal Institute of TechnologyManipalIndia
  2. 2.Department of Electronics and communicationM.I.T.E.MoodbidriIndia

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