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Efficient internal and surface fingerprint extraction and blending using optical coherence tomography

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Abstract

Optical coherence tomography provides a 3D representation of fingertip skin where surface and internal fingerprints are found. These fingerprints are topographically identical. However, the surface skin is prone to damage, distortion, and spoofing; and the internal fingerprint is difficult to access and extract. This research presents a novel scaling-resolution approach to fingerprint zone detection and extraction. Furthermore, a local-quality-based blending procedure is also proposed. The accuracy of the zone-detection algorithm is comparable to an earlier work, yielding a mean-squared error of 25.9 and structural similarity of 95.8% (compared to a ground-truth estimate). Blending the surface and internal fingerprints improved the National Institute of Science and Technology’s Fingerprint Image Quality scores and the average maximum match scores (when matched against conventional surface counterparts). The fingerprint blending procedure was able to combine high-quality regions from both fingerprints, thus mitigating surface wrinkles and anomalous poor-quality regions. Furthermore, spoof detection via a surface-to-internal fingerprint comparison was proposed and tested.

© 2015 Optical Society of America

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