Abstract
Fingerprint recognition is an important security technique with a steadily growing usage for the identification and verification of individuals. However, current fingerprint acquisition systems have certain disadvantages, which include the requirements of physical contact with the acquisition device, and the presence of undesirable artefacts, such as scars, on the surface of the fingerprint. This paper evaluates the accuracy of a complete framework for the capturing of undamaged, undistorted fingerprints from below the skins surface using optical coherence tomography hardware, the extraction and conversion of the subsurface data into a usable fingerprint and the matching of such fingerprints. The ability of the framework to integrate with existing fingerprint recognition systems and its ability to operate as an independent stand-alone system are both evaluated.
Keywords
- Optical Coherence Tomography
- Optical Coherence Tomography Image
- False Rejection Rate
- Optical Coherence Tomography Scanner
- Fingerprint Recognition
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Acknowledgements
Acknowledgments of support go to Dr. Christiaan van der Walt and Luke Darlow of the Council for Scientific and Industrial Research’s Modelling and Digital Science unit, and the CSIR National Laser Centre.
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Moolla, Y., Singh, A., Saith, E., Akhoury, S. (2015). Fingerprint Matching with Optical Coherence Tomography. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_22
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DOI: https://doi.org/10.1007/978-3-319-27863-6_22
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