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Usability of Skin Texture Biometrics for Mixed-Resolution Images

Alsufyani, Hamed, Hoque, Sanaul, Deravi, Farzin (2019) Usability of Skin Texture Biometrics for Mixed-Resolution Images. In: 2019 Eighth International Conference on Emerging Security Technologies (EST). 2019 Eighth International Conference on Emerging Security Technologies (EST). . IEEE ISBN 978-1-72815-546-3. (doi:10.1109/EST.2019.8806212) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:74615)

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https://doi.org/10.1109/EST.2019.8806212

Abstract

There is a growing demand for alternative biometric modalities that can handle various real world challenges such as recognising partially occluded individuals. Skin texture has been proposed as a potential alternative; however, such skin texture analysis can become difficult when captured images are at varying resolutions (due to different distances or devices). This paper explores the prospect of using mixed-resolution facial skin images as a source of biometric information. The four facial skin regions investigated here are the forehead, right cheek, left cheek, and chin which were selected because at least one of these are expected to be captured in real-world scenarios. The proposed framework first localises and assesses the usability of the extracted region of interest (ROI) for subsequent analysis. Local Binary Pattern (LBP) descriptors are then used for feature matching because of their reported effectiveness in extracting skin texture information. Experiments conducted using the XM2VTS database suggest that mixed resolution skin texture images can provide adequate information for biometric applications.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/EST.2019.8806212
Uncontrolled keywords: skin texture, forensic biometrics, occlusion
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Sanaul Hoque
Date Deposited: 26 Feb 2020 10:12 UTC
Last Modified: 27 Feb 2020 11:33 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/74615 (The current URI for this page, for reference purposes)
Hoque, Sanaul: https://orcid.org/0000-0001-8627-3429
Deravi, Farzin: https://orcid.org/0000-0003-0885-437X
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