1. Feature Of The Week 5/19/13: Using Optical Coherence Tomography For Anti-Spoof Fingerprint Detection

    Feature Of The Week 5/19/13: Using Optical Coherence Tomography For Anti-Spoof Fingerprint Detection

    Fingerprint biometrics, including automated fingerprint identification systems (AFIS), currently occupy two-thirds of the biometric market and are expected to remain the dominant player in this area. The technology can be integrated into small, compact devices and the instruments are relatively fast. However, the overall success of using fingerprints for identification and verification purposes greatly depends upon the quality of the fingerprints initially enrolled. For example, fingerprints captured from older people are significantly lower quality than those from younger people due primarily to ridge-wearing and difficulty of interacting effectively with conventional fingerprint scanners. The ramification is that the problem of obtaining prints of sufficient quality inexorably becomes worse as society ages. Whilst often noticed, spoof fingerprints can go undetected.

    We propose the use of correlation mapping optical coherence tomography (cmOCT) to deliver additional biometrics associated with the finger that could complement existing fingerprint technology for law enforcement applications. The current study extends the existing fingerprint paradigm by measuring additional biometrics associated with sub-surface finger tissue such as sub-surface fingerprints, sweat glands, and the pattern of the capillary bed to yield a user-friendly cost effective and anti- spoof multi-mode biometric solution associated with the finger. To our knowledge no other method has been able to capture sub-surface fingerprint, papillary pattern and horizontal vessel pattern in a single scan or to show the correspondence between these patterns in live adult human fingertip. Unlike many current technologies this approach incorporates ‘liveness’ testing by default. The ultimate output is a biometric module which is difficult to defeat and complements fingerprint scanners that currently are used in border control and law enforcement applications.

    For more information see recent Article. Courtesy of Azhar Zam from National University of Ireland, Galway.

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