Touchless Fingerprint Sample Quality: Prerequisites for the Applicability of NFIQ2.0

Abstract

The impact of fingerprint sample quality on biometric performance is undisputed. For touch-based fingerprint data, the effectiveness of the NFIQ2.0 quality estimation method is well documented in scientific literature. Due to the increasing use of touchless fingerprint recognition systems a thorough investigation of the usefulness of the NFIQ2.0 for touchless fingerprint data is of interest. In this work, we investigate whether NFIQ2.0 quality scores are predictive of error rates associated with the biometric performance of touchless fingerprint recognition. For this purpose, we propose a touchless fingerprint preprocessing that favours NFIQ2.0 quality estimation which has been designed for touch-based fingerprint data. Comparisons are made between NFIQ2.0 score distributions obtained from touch-based and touchless fingerprint data of the publicly available FVC06, MCYT, PolyU, and ISPFDv1 databases. Further, the predictive power regarding biometric performance is evaluated in terms of Error-versus-Reject Curves (ERCs) using an open source fingerprint recognition system. Under constrained capture conditions NFIQ2.0 is found to be an effective tool for touchless fingerprint quality estimation if an adequate preprocessing is applied.