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Survey of Face Recognition Techniques

by Nilima B. Kachare, Vandana S. Inamdar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 19
Year of Publication: 2010
Authors: Nilima B. Kachare, Vandana S. Inamdar
10.5120/408-604

Nilima B. Kachare, Vandana S. Inamdar . Survey of Face Recognition Techniques. International Journal of Computer Applications. 1, 19 ( February 2010), 29-33. DOI=10.5120/408-604

@article{ 10.5120/408-604,
author = { Nilima B. Kachare, Vandana S. Inamdar },
title = { Survey of Face Recognition Techniques },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 19 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number19/408-604/ },
doi = { 10.5120/408-604 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:46:52.361465+05:30
%A Nilima B. Kachare
%A Vandana S. Inamdar
%T Survey of Face Recognition Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 19
%P 29-33
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face recognition is a kind of automated biometric identification technique that recognizes an individual based on their facial features as essential elements of distinction. The research on face recognition has been actively going on in the recent years because face recognition spans numerous fields and disciplines such as access control, surveillance and security, credit-card verification, criminal identification and digital library. In this paper we discuss past research on biometric face feature extraction and recognition of static images. We will present implementation outline of these methods along with their comparative measures.

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Index Terms

Computer Science
Information Sciences

Keywords

Automatic face recognition Appearance based recognition Principal component Feature extraction Maximum likelihood Hidden Markov Model Based method (HMM) statistical approaches template based approaches) and feature based methods eigenface fisherface Fisher's Linear Discriminant (FLD) Gabor Filter Gabor Coefficients

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