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Face Recognition based on Oriented Complex Wavelets and FFT

by Rangaswamy Y, Raja K B, Venugopal K R
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 24
Year of Publication: 2015
Authors: Rangaswamy Y, Raja K B, Venugopal K R
10.5120/21386-4396

Rangaswamy Y, Raja K B, Venugopal K R . Face Recognition based on Oriented Complex Wavelets and FFT. International Journal of Computer Applications. 119, 24 ( June 2015), 27-34. DOI=10.5120/21386-4396

@article{ 10.5120/21386-4396,
author = { Rangaswamy Y, Raja K B, Venugopal K R },
title = { Face Recognition based on Oriented Complex Wavelets and FFT },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 24 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 27-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number24/21386-4396/ },
doi = { 10.5120/21386-4396 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:55.660380+05:30
%A Rangaswamy Y
%A Raja K B
%A Venugopal K R
%T Face Recognition based on Oriented Complex Wavelets and FFT
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 24
%P 27-34
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Face is a physiological Biometric trait used in Biometric System. In this paper face recognition using oriented complex wavelets and Fast Fourier Transform (FROCF) is proposed. The five-level Dual Tree Complex Wavelet Transform(DTCWT) is applied on face images to get shift invariant and directional features along ±15o ,± 45o and ± 75o angular directions. The different pose, illumination and expression variations of face images are represented in frequency domain using Fast Fourier Transform(FFT) resulting in FFT features. Features of DTCWT and FFT are fused by arithmetic addition to get final features. Euclidean Distance classifier is applied to the features to recognize the genuine and imposter faces. The Performance analysis of proposed method is tested with ORL, JAFFE, L-SPACEK and CMU-PIE having different illumination and pose conditions. The Results shows that Recognition Rate of proposed FROCF is better compared to Existing Recognition Methods.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Face Recognition DTCWT FFT TSR

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