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Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks

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Main Author: Sundaraj, Kenneth
Other Authors: kenneth@unimap.edu.my
Format: Article
Language:English
Published: World Scientific and Engineering Academy and Society (WSEAS) Press 2009
Subjects:
Eigenfaces
Face biometrics
Face recognition
Facial artifacts
Biometrics
Image processing > Digital techniques
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/7433
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spelling my.unimap-74332009-12-29T07:15:34Z Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks Sundaraj, Kenneth kenneth@unimap.edu.my Eigenfaces Face biometrics Face recognition Facial artifacts Biometrics Image processing -- Digital techniques Link to publisher's homepage at http://www.worldses.org Biometrics has been an important issue pertaining to security in the last few decades. Departments or agencies entrusted with national security are increasingly installing surveillance cameras in strategic or critical areas to monitor the identities of the general public. Upon locating suspicious characters in the video feed, they are compared with existing databases to find a match. These databases are generally compiled from the National Registration Department (NRD), Immigration, intelligence agencies, etc. Unfortunately, as mentioned in most reports of tragic events, suspicious characters do not resemble anything like what has been stored in the databases. There is a high chance that the face biometric identification software will miss these culprits. In this paper we propose to investigate the effects of facial artifacts on the recognition rate of eigenface based neural networks. It has been found that eigenfaces coupled with Euclidean distance can be successfully used to recognize the human face in almost real-time. However, facial artifacts can cause the features that characterize a face to be distorted. Hence, it is desirable to identify problematic facial artifacts that can cause false identification or no identification. The main focus of this paper is the investigation of common facial artifacts on the performance of recognition and the proposition of modification to existing databases to improve the positive rate of identification. A professional graphic artist was used to modify the images used in the experiments. We use a single and multiple eigenface based neural network as the classifier in our experiments. 2009-12-29T07:15:34Z 2009-12-29T07:15:34Z 2009 Article WSEAS Transactions on Systems, vol.8 (1), 2009, pages 127-136. 1109-2777 http://portal.acm.org/citation.cfm?id=1513545 http://hdl.handle.net/123456789/7433 en World Scientific and Engineering Academy and Society (WSEAS) Press
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Eigenfaces
Face biometrics
Face recognition
Facial artifacts
Biometrics
Image processing -- Digital techniques
spellingShingle Eigenfaces
Face biometrics
Face recognition
Facial artifacts
Biometrics
Image processing -- Digital techniques
Sundaraj, Kenneth
Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
description Link to publisher's homepage at http://www.worldses.org
author2 kenneth@unimap.edu.my
author_facet kenneth@unimap.edu.my
Sundaraj, Kenneth
format Article
author Sundaraj, Kenneth
author_sort Sundaraj, Kenneth
title Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
title_short Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
title_full Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
title_fullStr Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
title_full_unstemmed Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
title_sort investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks
publisher World Scientific and Engineering Academy and Society (WSEAS) Press
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/7433
_version_ 1643788812600475648
score 13.214268

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