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Contactless robust 3D palm-print identification using photometric stereo

Smith, Lyndon N.; Langhof, Max P.; Hansen, Mark F.; Smith, Melvyn L.

Authors

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine

Max P. Langhof

Mark Hansen Mark.Hansen@uwe.ac.uk
Professor of Machine Vision and Machine Learning

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof



Abstract

Palmprints are of considerable interest as a reliable biometric, since they offer significant advantages, such as greater user acceptance than fingerprint or iris recognition. 2D systems can be spoofed by a photograph of a hand; however, 3D avoids this by recovering and analysing 3D textures and profiles. 3D palmprints can also be captured in a contactless manner, which is critical for ensuring hygiene (something that is particularly important in relation to pandemics such as COVID-19), and ease of use. The gap in prior work, between low resolution wrinkle studies and high-resolution palmprint recognition, is bridged here using high-resolution non-contact photometric stereo. A camera and illuminants are synchronised with image capture to recover high-definition 3D texture data from the palm, which are then analysed to extract ridges and wrinkles. This novel low-cost approach, which can tolerate distortions inherent to unconstrained contactless palmprint acquisition, achieved a 0.1% equ

Citation

Smith, L. N., Langhof, M. P., Hansen, M. F., & Smith, M. L. (2021). Contactless robust 3D palm-print identification using photometric stereo. https://doi.org/10.1117/12.2595439

Conference Name Applications of Digital Image Processing XLIV
Conference Location San Diego, United States
Start Date Aug 1, 2021
End Date Aug 5, 2021
Acceptance Date May 7, 2021
Publication Date Aug 1, 2021
Deposit Date Sep 9, 2021
Publisher Society of Photo-optical Instrumentation Engineers
Volume 11842
Series Title SPIE Optical Engineering + Applications, 2021
Series Number Volume 1184227
ISBN 9781510645226
DOI https://doi.org/10.1117/12.2595439
Keywords 3D machine vision; biometrics (access control); feature extraction; image texture analysis, palmprint recognition
Public URL https://uwe-repository.worktribe.com/output/7746147
Publisher URL https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11842/1184227/Contactless-robust-3D-palm-print-identification-using-photometric-stereo/10.1117/12.2595439.short?SSO=1
Additional Information Mathematics Subject Classification (MSC) code:
68T45 Machine vision and scene understanding

Journal of Economic Literature (JEL) code:
L86 Information and Internet Services; Computer Software

Acknowledgements:
This work was supported in part by a UWE Vice Chancellor Early Career Research Award, which was awarded to M. Hansen. Full name of the funding body is: University of the West of England, Bristol.