MCLFIQ: Mobile Contactless Fingerprint Image Quality
- URL: http://arxiv.org/abs/2304.14123v2
- Date: Tue, 12 Dec 2023 09:45:00 GMT
- Title: MCLFIQ: Mobile Contactless Fingerprint Image Quality
- Authors: Jannis Priesnitz, Axel Wei{\ss}enfeld, Laurenz Ruzicka, Christian
Rathgeb, Bernhard Strobl, Ralph Lessmann, Christoph Busch
- Abstract summary: We re-trained the NIST Fingerprint Image Quality (NFIQ) 2 method, which was originally designed for contact-based fingerprints, with a synthetic contactless fingerprint database.
We evaluate the predictive performance of the resulting MCLFIQ model in terms of Error-vs.-Discard Characteristic curves on three real-world contactless fingerprint databases.
- Score: 6.041268643935127
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: We propose MCLFIQ: Mobile Contactless Fingerprint Image Quality, the first
quality assessment algorithm for mobile contactless fingerprint samples. To
this end, we re-trained the NIST Fingerprint Image Quality (NFIQ) 2 method,
which was originally designed for contact-based fingerprints, with a synthetic
contactless fingerprint database. We evaluate the predictive performance of the
resulting MCLFIQ model in terms of Error-vs.-Discard Characteristic (EDC)
curves on three real-world contactless fingerprint databases using three
recognition algorithms. In experiments, the MCLFIQ method is compared against
the original NFIQ 2.2 method, a sharpness-based quality assessment algorithm
developed for contactless fingerprint images \rev{and the general purpose image
quality assessment method BRISQUE. Furthermore, benchmarks on four
contact-based fingerprint datasets are also conducted.}
Obtained results show that the fine-tuning of NFIQ 2 on synthetic contactless
fingerprints is a viable alternative to training on real databases. Moreover,
the evaluation shows that our MCLFIQ method works more accurate and robust
compared to all baseline methods on contactless fingerprints. We suggest
considering the proposed MCLFIQ method as a \rev{starting point for the
development of} a new standard algorithm for contactless fingerprint quality
assessment.
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