Merkle, JohannesSchwaiger, MichaelBreitenstein, MarcoBausinger, OliverElwart, KristinaNuppeney, MarkusBrömme, ArslanBusch, Christoph2019-01-172019-01-172010978-3-88579-258-1https://dl.gi.de/handle/20.500.12116/19566The NIST Fingerprint Image Quality (NFIQ) algorithm has become a standard method to assess fingerprint image quality. However, in many applications a more accurate and reliable assessment is desirable. In this publication, we report on our efforts to optimize the NFIQ algorithm by a re-training of the underlying neural network based on a large fingerprint image database. Although we only achieved a marginal improvement, our work has revealed several areas for potential optimization.enText/Conference Paper1617-5468