Comparison of PCA and 2D-PCA on Indian Faces

Author

Rajendran, S. ; Kaul, A. ; Nath, R. ; Arora, A.S. ; Chauhan, Shubhika

Author_Institution

Electr. Eng. Dept., Nat. Inst. of Technol. Hamirpur, Hamirpur, India

fYear

2014

fDate

12-13 July 2014

Firstpage

561

Lastpage

566

Abstract

Face recognition is an extensively researched topic by researchers from diverse disciplines. Several unsupervised statistical feature extraction methods have been used in face recognition, out of these in this paper a comparison of the PCA(eigenfaces) and 2D-PCA approaches on Indian Faces has been presented. To test and compare their performances a series of experiments were performed on ORL database, Yale face database and then on an in-house dataset which has been collected over a span of 6 months. The performance parameters compared here are recognition rate and speed with varying number of training images. The application of various preprocessing techniques which can be used to improve their performance has also been studied.

Keywords

face recognition; feature extraction; principal component analysis; 2D-PCA; Indian faces; ORL database; PCA; Yale face database; face recognition; in-house dataset; preprocessing techniques; principal component analysis; unsupervised statistical feature extraction methods; Biomedical imaging; Face recognition; Hair; Image recognition; Principal component analysis; Training; 2D-PCA; Eigenfaces; Indian faces; PCA; Preprocessing techniques; Two-Dimensional PCA; face recognition; unsupervised statistical feature extraction;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Propagation and Computer Technology (ICSPCT), 2014 International Conference on

Conference_Location

Ajmer

Print_ISBN

978-1-4799-3139-2

Type

conf

DOI

10.1109/ICSPCT.2014.6884932

Filename

6884932