Design of anti-spoofing system for face recognition

Of the many types of cyber-security measures today, biometrics stands out as one of the most intriguing, with great potential to be explored. The advancement of technology means that threats and the ways one can attack is increasing. Face spoofing detection is one way to overcome the attack of spoof...

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Main Author: Ang, Alexandrea Shiying
Other Authors: Chang Chip Hong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/136594
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1365942023-07-07T18:08:59Z Design of anti-spoofing system for face recognition Ang, Alexandrea Shiying Chang Chip Hong School of Electrical and Electronic Engineering ECHChang@ntu.edu.sg Engineering Engineering::Electrical and electronic engineering Of the many types of cyber-security measures today, biometrics stands out as one of the most intriguing, with great potential to be explored. The advancement of technology means that threats and the ways one can attack is increasing. Face spoofing detection is one way to overcome the attack of spoofing. However, the current methods of anti-spoofing via facial recognition utilises only the light (luminance) aspect of images, without paying much attention to the chrominance or colour part. This report therefore seeks to implement and prove the functionality of a new methodology- one that involves the heavy emphasis of chrominance, through colour texture analysis. This is done using the Michigan State University’s Mobile Face Spoofing Database (MSU MFSD) and MATLAB. The results of these experiments are then compared and concluded against its literature derivation. At the end, the potential for using Deep Learning Methodology is introduced. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-01-06T02:49:27Z 2020-01-06T02:49:27Z 2019 Final Year Project (FYP) https://hdl.handle.net/10356/136594 en A2271-182 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Engineering::Electrical and electronic engineering
spellingShingle Engineering
Engineering::Electrical and electronic engineering
Ang, Alexandrea Shiying
Design of anti-spoofing system for face recognition
description Of the many types of cyber-security measures today, biometrics stands out as one of the most intriguing, with great potential to be explored. The advancement of technology means that threats and the ways one can attack is increasing. Face spoofing detection is one way to overcome the attack of spoofing. However, the current methods of anti-spoofing via facial recognition utilises only the light (luminance) aspect of images, without paying much attention to the chrominance or colour part. This report therefore seeks to implement and prove the functionality of a new methodology- one that involves the heavy emphasis of chrominance, through colour texture analysis. This is done using the Michigan State University’s Mobile Face Spoofing Database (MSU MFSD) and MATLAB. The results of these experiments are then compared and concluded against its literature derivation. At the end, the potential for using Deep Learning Methodology is introduced.
author2 Chang Chip Hong
author_facet Chang Chip Hong
Ang, Alexandrea Shiying
format Final Year Project
author Ang, Alexandrea Shiying
author_sort Ang, Alexandrea Shiying
title Design of anti-spoofing system for face recognition
title_short Design of anti-spoofing system for face recognition
title_full Design of anti-spoofing system for face recognition
title_fullStr Design of anti-spoofing system for face recognition
title_full_unstemmed Design of anti-spoofing system for face recognition
title_sort design of anti-spoofing system for face recognition
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/136594
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