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Face Recognition using Template Matching

by Amandeep Kour
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 8
Year of Publication: 2015
Authors: Amandeep Kour
10.5120/20170-2329

Amandeep Kour . Face Recognition using Template Matching. International Journal of Computer Applications. 115, 8 ( April 2015), 10-13. DOI=10.5120/20170-2329

@article{ 10.5120/20170-2329,
author = { Amandeep Kour },
title = { Face Recognition using Template Matching },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 8 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 10-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number8/20170-2329/ },
doi = { 10.5120/20170-2329 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:54:15.061506+05:30
%A Amandeep Kour
%T Face Recognition using Template Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 8
%P 10-13
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The traditional approach towards human identification such as fingerprints, identity cards, iris recognition etc. lead to the improvised technique for face recognition. This includes enhancement and segmentation of face image, detection of face boundary and facial features, matching of extracted features against the features in a database, and finally recognition of the face. This research proposes a wavelet transformation for preprocessing the face image, extracting edge image, extracting features and finally matching extracted facial features for face recognition. Simulation is done using ORL database that contains PGM images. This research finds application in homeland security where it can increase the robustness of the existing face recognition algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

Face recognition Wavelet transformation edge image extraction feature extraction match features

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