Compact and Mobile Full-Field Optical Coherence Tomography Sensor for Subsurface Fingerprint Imaging

Conventional fingerprint sensors that are deployed in real-life applications lack the ability to peer inside a finger beyond the external surface. Subsurface information can provide complimentary biometric characteristics associated with the finger. The subsurface fingerprints can also be employed w...

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Veröffentlicht in:IEEE access 2020, Vol.8, p.15194-15204
Hauptverfasser: Auksorius, Egidijus, Raja, Kiran B., Topcu, Berkay, Ramachandra, Raghavendra, Busch, Christoph, Boccara, Claude A.
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Sprache:eng
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Zusammenfassung:Conventional fingerprint sensors that are deployed in real-life applications lack the ability to peer inside a finger beyond the external surface. Subsurface information can provide complimentary biometric characteristics associated with the finger. The subsurface fingerprints can also be employed when the quality of the external/surface fingerprints is affected. One of the most promising technologies for imaging below the surface of an external fingerprint is full-field optical coherent tomography (FF-OCT). However, the FF-OCT can be expensive and cumbersome, despite its proven ability for biometric use. In this paper, we describe the design and implementation of a compact, mobile and cost-effective FF-OCT sensor that is stable and easy to use. The newly designed sensor, being 30 cm × 30 cm × 10 cm in size, comprises of a dedicated silicon camera, stable Michelson interferometer and a bright Near-Infra-Red (NIR) light emitting diode. It enables recording of 1.7 cm × 1.7 cm images of subsurface finger features, such as internal fingerprints and sweat ducts. We show the employability of the newly designed sensor for different applications. Specifically, we validate its usefulness by capturing subsurface fingerprints of 585 subjects leading to 3510 unique fingerprints. The resulting accuracy of 0.74% as Equal Error Rate (EER) indicates the backward compatibility of the proposed sensor with the existing commercial off-the-shelf algorithms. Thanks to the large fingerprint database collected in this work we determined the most useful imaging depth for the fingerprint matching purposes to be around 100 gym. As an additional advantage, the sensor could be readily used in other applications with little or no modification, such as in vivo skin imaging.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2966241