Literature DB >> 17151765

Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis.

Yezeng Cheng1, Kirill V Larin.   

Abstract

Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

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Year:  2006        PMID: 17151765     DOI: 10.1364/ao.45.009238

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  5 in total

1.  Fingerprint imaging from the inside of a finger with full-field optical coherence tomography.

Authors:  Egidijus Auksorius; A Claude Boccara
Journal:  Biomed Opt Express       Date:  2015-10-20       Impact factor: 3.732

Review 2.  Towards automated classification of clinical optical coherence tomography data of dense tissues.

Authors:  Florian Bazant-Hegemark; Nicholas Stone
Journal:  Lasers Med Sci       Date:  2008-10-21       Impact factor: 3.161

3.  Optical sensing method for screening disease in melon seeds by using optical coherence tomography.

Authors:  Changho Lee; Seung-Yeol Lee; Jeong-Yeon Kim; Hee-Young Jung; Jeehyun Kim
Journal:  Sensors (Basel)       Date:  2011-10-10       Impact factor: 3.576

4.  Ratiometric Impedance Sensing of Fingers for Robust Identity Authentication.

Authors:  Hyung Wook Noh; Chang-Geun Ahn; Hyoun-Joong Kong; Joo Yong Sim
Journal:  Sci Rep       Date:  2019-09-19       Impact factor: 4.379

5.  Electrical Impedance of Upper Limb Enables Robust Wearable Identity Recognition against Variation in Finger Placement and Environmental Factors.

Authors:  Hyung Wook Noh; Joo Yong Sim; Chang-Geun Ahn; Yunseo Ku
Journal:  Biosensors (Basel)       Date:  2021-10-16
  5 in total

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