A Novel Face Recognition Method Using PCA, LDA and Support Vector Machine

U. Raghavendra; P. Mahesh; Anjan Gudigar

Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II

Research Article

A Novel Face Recognition Method Using PCA, LDA and Support Vector Machine

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@INPROCEEDINGS{10.1007/978-3-642-27308-7_25,
    author={U. Raghavendra and P. Mahesh and Anjan Gudigar},
    title={A Novel Face Recognition Method Using PCA, LDA and Support Vector Machine},
    proceedings={Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II},
    proceedings_a={CCSIT PATR II},
    year={2012},
    month={11},
    keywords={Dimension Reduction Feature Extraction Classification Support Vector Machine},
    doi={10.1007/978-3-642-27308-7_25}
}

U. Raghavendra
P. Mahesh
Anjan Gudigar
Year: 2012
A Novel Face Recognition Method Using PCA, LDA and Support Vector Machine
CCSIT PATR II
Springer
DOI: 10.1007/978-3-642-27308-7_25

U. Raghavendra¹^,*, P. Mahesh²^,*, Anjan Gudigar²^,*

1: Manipal Institute of Technology
2: M.I.T.E.

*Contact email: raghu_u109@rediffmail.com, mahesh24pk@gmail.com, anjangudigar83@gmail.com

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

Published: 2012-11-09

: http://dx.doi.org/10.1007/978-3-642-27308-7_25