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Moisture-insensitive optical fingerprint scanner based on polarization resolved in-finger scattered light
Author(s) -
Seon-Woo Back,
Yong-Geon Lee,
SangShin Lee,
GeunSik Son
Publication year - 2016
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.24.019195
Subject(s) - optics , scanner , materials science , refractive index , light scattering , fingerprint (computing) , wavelength , scattering , fingerprint recognition , physics , computer science , artificial intelligence
A moisture-insensitive optical fingerprint scanner (FPS) that is based on polarization resolved in-finger light is proposed and realized. Incident visible light, which is selectively fed to a fingerprint sample via a polarization beam splitter (PBS), is deemed to be partially scattered backward by tissues associated with the skin of the finger. The backscattered light is mostly index-guided in the ridge comprising the fingerprint, which has a higher refractive index, and is drastically dispersed in the valley, which is typically filled with water or air and so has a lower index. However, when light reflects directly off the surface of the finger skin, it fundamentally prevents the scanned image from being determined. The proposed FPS produces bright and dark intensity patterns that are alternately created on the surface of the PBS and correspond to the ridges and valleys, respectively. Thus, this method can especially distinguish between a fake synthetic fingerprint and a genuine fingerprint due to its use of in-finger scattered light. The scanner has been rigorously designed by carrying out ray-optic simulations depending on the wavelength, with tissue-induced scattering taken into account. The device was constructed by incorporating a wire-grid type PBS in conjunction with visible LED sources, including blue, green and red. The scanner adopting a blue LED, which exhibits the strongest light scattering, resulted in the best fingerprint image, enabling enhanced fidelity under the wet and dry situations. Finally, a fake synthetic fingerprint could be successfully discriminated.

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