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Automated Skin Region Quality Assessment for Texture-based Biometrics

Alsufyani, Hamed, Hoque, Sanaul, Deravi, Farzin (2017) Automated Skin Region Quality Assessment for Texture-based Biometrics. In: 2017 Seventh International Conference on Emerging Security Technologies (EST). . pp. 169-174. IEEE ISBN 978-1-5386-4019-7. E-ISBN 978-1-5386-4018-0. (doi:10.1109/EST.2017.8090418) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:63349)

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Abstract

Designing a biometric system based solely on skin texture is of interest because the face is sometimes occluded by hair or artefacts in many real-world contexts. This work presents a novel framework for the assessment of skin-based biometric systems incorporating skin quality information. The quality or purity of the extracted skin region is automatically established using pixel colour models prior to biometric processing. Facial landmarks are detected to facilitate automated extraction of facial regions of interest. Although the present study is confined to the forehead region, the idea can be extended to other skin regions. Local Binary Patterns (LBP) and Gabor wavelet filters are utilised to extract skin features. Using the publicly available XM2VTS database, the experimental results show that the system provides promising performance when compared to other commonly used techniques.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/EST.2017.8090418
Uncontrolled keywords: skin textures; skin biometrics; skin detection; facial marks
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Farzin Deravi
Date Deposited: 09 Sep 2017 10:20 UTC
Last Modified: 16 Feb 2021 13:48 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/63349 (The current URI for this page, for reference purposes)

University of Kent Author Information

Alsufyani, Hamed.

Creator's ORCID:
CReDIT Contributor Roles:

Hoque, Sanaul.

Creator's ORCID: https://orcid.org/0000-0001-8627-3429
CReDIT Contributor Roles:

Deravi, Farzin.

Creator's ORCID: https://orcid.org/0000-0003-0885-437X
CReDIT Contributor Roles:
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