A PCA-based Face Recognition Method by Applying Fast Fourier Transform in Pre-processing

DOI

10.2991/icmt-13.2013.141How to use a DOI?

Keywords

Face recognition; pre-processing; Fast Fourier Transform; PCA; SVM

Abstract

Principal Component Analysis (PCA) is a well-studied method in face recognition. Noticing that few researches focus on pre-processing of images, which will also improve the performance of feature extraction of PCA algorithm, we present an improved approach of PCA based face recognition algorithm using Fast Fourier Transform (FFT). In our method, FFT is presented as a method to combine amplitude spectrum of one image with phase spectrum of another image as a mixed image. PCA is applied to do feature extraction and a kernel SVM is harnessed as a classifier. To test and evaluate the performance of the proposed approach, a series of experiments are performed on Yale face database A. The experimental results show that our proposed method is encouraging.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhang Dehai
AU  - Ding Da
AU  - Li Jin
AU  - Liu Qing
PY  - 2013/11
DA  - 2013/11
TI  - A PCA-based Face Recognition Method by Applying Fast Fourier Transform in Pre-processing
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 1148
EP  - 1155
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.141
DO  - 10.2991/icmt-13.2013.141
ID  - Dehai2013/11
ER  -