Fingerprint recognition is one of the dominant methods among all biometric techniques. However, current commercial fingerprint reader systems are based on analysis of surface topography of a finger and, thus, have tremendous security vulnerability for simply made artificial fingerprint dummies. In this letter, we demonstrate that a novel optical coherence tomography-based method for depth-resolved 2-D and 3-D imaging and assessment of artificial and real fingerprints could significantly enhance spoof-proofing of fingerprint reader systems as well as provide information of both artificial and real ridge and furrow patterns (that form the fingerprint patterns) simultaneously.
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Kirill V. Larin (2007) studied this question.
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