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Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging

Spoofing is an act to impersonate a valid user of any biometric systems in order to gain access. In a face biometric system, an imposter might use some fake masks that mimic the real user face. Existing countermeasures against spoofing adopt face texture analysis, motion detection and surface re...

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Main Authors: Azim Zaliha, Abd Aziz, Wei, Hong, Ferryman, James
Format: Conference or Workshop Item
Language:English
Published: 2017
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.unisza.edu.my/787/1/FH03-FIK-18-15467.pdf
http://eprints.unisza.edu.my/787/
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spelling my-unisza-ir.7872020-10-27T06:45:07Z http://eprints.unisza.edu.my/787/ Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging Azim Zaliha, Abd Aziz Wei, Hong Ferryman, James QA75 Electronic computers. Computer science Spoofing is an act to impersonate a valid user of any biometric systems in order to gain access. In a face biometric system, an imposter might use some fake masks that mimic the real user face. Existing countermeasures against spoofing adopt face texture analysis, motion detection and surface reflection analysis. For the purpose of face anti-spoofing analysis, skin structure is a key factor in achieving the target of our study. Skin consists of multiple layers structure which produces multiple reflections: surface and subsurface reflections. In this paper, we proposed a measure to discriminate between a genuine face and a printed paper photo based on physical properties of the materials which contribute to its distinctive reflection values. In order to differentiate the reflections, polarized light (light that vibrates in a single direction) can be used. The Stokes parameters are applied to generate the Stokes images which are then used to produce the final image known as Stokes degree of linear polarization (SDOLP) image. The intensity of the SDOLP image is investigated statistically which has shown promising results in the materials classification, between the skin and the paper mask. Furthermore, comparison between the experimental results from two skin color groups, black and others show that the SDOLP data distribution of black skin is similar to the printed paper photo of the same skin group. 2017 Conference or Workshop Item NonPeerReviewed text en http://eprints.unisza.edu.my/787/1/FH03-FIK-18-15467.pdf Azim Zaliha, Abd Aziz and Wei, Hong and Ferryman, James (2017) Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging. In: 2017 5th International Workshop on Biometrics and Forensics (IWBF), 29 May 2017, UNITED KINGDOM.
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Azim Zaliha, Abd Aziz
Wei, Hong
Ferryman, James
Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging
description Spoofing is an act to impersonate a valid user of any biometric systems in order to gain access. In a face biometric system, an imposter might use some fake masks that mimic the real user face. Existing countermeasures against spoofing adopt face texture analysis, motion detection and surface reflection analysis. For the purpose of face anti-spoofing analysis, skin structure is a key factor in achieving the target of our study. Skin consists of multiple layers structure which produces multiple reflections: surface and subsurface reflections. In this paper, we proposed a measure to discriminate between a genuine face and a printed paper photo based on physical properties of the materials which contribute to its distinctive reflection values. In order to differentiate the reflections, polarized light (light that vibrates in a single direction) can be used. The Stokes parameters are applied to generate the Stokes images which are then used to produce the final image known as Stokes degree of linear polarization (SDOLP) image. The intensity of the SDOLP image is investigated statistically which has shown promising results in the materials classification, between the skin and the paper mask. Furthermore, comparison between the experimental results from two skin color groups, black and others show that the SDOLP data distribution of black skin is similar to the printed paper photo of the same skin group.
format Conference or Workshop Item
author Azim Zaliha, Abd Aziz
Wei, Hong
Ferryman, James
author_facet Azim Zaliha, Abd Aziz
Wei, Hong
Ferryman, James
author_sort Azim Zaliha, Abd Aziz
title Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging
title_short Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging
title_full Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging
title_fullStr Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging
title_full_unstemmed Face anti-spoofing countermeasure: Efficient 2D materials classification using polarization imaging
title_sort face anti-spoofing countermeasure: efficient 2d materials classification using polarization imaging
publishDate 2017
url http://eprints.unisza.edu.my/787/1/FH03-FIK-18-15467.pdf
http://eprints.unisza.edu.my/787/
_version_ 1683234929689755648
score 13.211869

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