Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/136594
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ang, Alexandrea Shiying | en_US |
dc.date.accessioned | 2020-01-06T02:49:27Z | - |
dc.date.available | 2020-01-06T02:49:27Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | https://hdl.handle.net/10356/136594 | - |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Nanyang Technological University | en_US |
dc.relation | A2271-182 | en_US |
dc.subject | Engineering | en_US |
dc.subject | Engineering::Electrical and electronic engineering | en_US |
dc.title | Design of anti-spoofing system for face recognition | en_US |
dc.type | Final Year Project (FYP) | en_US |
dc.contributor.supervisor | Chang Chip Hong | en_US |
dc.contributor.school | School of Electrical and Electronic Engineering | en_US |
dc.description.degree | Bachelor of Engineering (Electrical and Electronic Engineering) | en_US |
dc.contributor.supervisoremail | ECHChang@ntu.edu.sg | en_US |
item.grantfulltext | restricted | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | EEE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ALEXANDREA FYP 17122019.pdf Restricted Access | 1.12 MB | Adobe PDF | View/Open |
Page view(s)
338
Updated on Apr 27, 2025
Download(s)
30
Updated on Apr 27, 2025
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.