  The 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.
