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Face Recognition using Gabor Filter based Feature Vector for Mobile Phones

Published on June 2013 by H. B. Kekre, Vinayak Ashok Bharadi
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International Conference and workshop on Advanced Computing 2013
Foundation of Computer Science USA
ICWAC - Number 2
June 2013
Authors: H. B. Kekre, Vinayak Ashok Bharadi
bf3ef2db-adf0-46bd-87a6-8ee789f6e9f2

H. B. Kekre, Vinayak Ashok Bharadi . Face Recognition using Gabor Filter based Feature Vector for Mobile Phones. International Conference and workshop on Advanced Computing 2013. ICWAC, 2 (June 2013), 0-0.

@article{
author = { H. B. Kekre, Vinayak Ashok Bharadi },
title = { Face Recognition using Gabor Filter based Feature Vector for Mobile Phones },
journal = { International Conference and workshop on Advanced Computing 2013 },
issue_date = { June 2013 },
volume = { ICWAC },
number = { 2 },
month = { June },
year = { 2013 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/icwac/number2/482-1316/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and workshop on Advanced Computing 2013
%A H. B. Kekre
%A Vinayak Ashok Bharadi
%T Face Recognition using Gabor Filter based Feature Vector for Mobile Phones
%J International Conference and workshop on Advanced Computing 2013
%@ 2249-0868
%V ICWAC
%N 2
%P 0-0
%D 2013
%I International Journal of Applied Information Systems
Abstract

Face Recognition Systems are becoming ubiquitous and inevitable in today's world. Being less intrusive and universal face recognition systems serve as good option for access control and surveillance. Here we are proposing a simple biometric system based on face authentication for access control of a handheld device like mobile phone or pocket pc. The propose systems hardware requirements are very low and it uses Gabor Filter based feature vector for face recognition. The proposed system uses simpler matching method and less computational overhead. The proposed systems accuracy is high for lower number of users; hence it is suitable for handheld devices as the accessing population is less. We have successfully tested this method on handheld device and results are presented here.

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Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Face recognition Image processing Gabor Filters Handheld Devices