Digital voting logic for manufacturable finger asperity wafer-scale solid state palm print scan devices

Abstract

Techniques are disclosed herein for artificial intelligence machine learning to increase collection of digital livescan fingerprints. According to certain embodiments of the invention, processing parameters can be automatically machine-optimized for processing scan images of fingerprints (and other areas) to increase the amount of detected minutia. The processing parameters can alter and change over time to reflect historical successes and failures of particular optimizations. This allows a fingerprint collection device to learn over time and become more accurate (i.e., more successful at detecting minutia). Additionally, the techniques further include receiving input from a user regarding physical traits of a scanned subject, to further customize the processing parameter optimization. Various other features are provided herein.