Subsurface and Layer Intertwined Template Protection Using Inherent Properties of Full-Field Optical Coherence Tomography Fingerprint Imaging

Kiran B. Raja, Ramachandra Raghavendra, Egidijus Auksorius, Christoph Busch; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, pp. 0-0

The emergence of Full Field-Optical Coherence Tomography (FF-OCT) for fingerprint imaging has shown it's ability in addressing and solving the drawbacks of traditional fingerprinting solutions such as spoofing attacks, low accuracy for abraded fingerprint. With the availability of multiple internal fingerprints (from subsurface captured at different depths), it is also essential to consider the aspects of ideal biometrics where the privacy of the fingerprint data is preserved. In this work, we propose a new framework for fingerprint template protection, highly customized to FF-OCT by exploring the interplay between subsurface. As a first of it's kind work attempting template protection for FF-OCT fingerprints, we explore deeply learnt features to derive first level of template for subsurface fingerprint image. We further propose to intertwine subsurface level templates to provide better and robust templates. With the set of extensive experiments on a FF-OCT fingerprint database of 200 unique fingerprints with a total of 2400 images, we demonstrate reliable biometric performance resulting in EER of 5.69% for unprotected template at first layer (subsurface) of fingerprint in FF-OCT, an EER of 5.86% for the protected templates at same layer and EER of 5.08% with the final protected templates with proposed intertwining of subsurface fingerprint. Further, through the security analysis, we also validate the strength of the proposed approach with near ideal unlinkability.