  This work presents an automated touchless fingerprint recognition system for
smartphones. We provide a comprehensive description of the entire recognition
pipeline and discuss important requirements for a fully automated capturing
system. Also, our implementation is made publicly available for research
purposes. During a database acquisition, a total number of 1,360 touchless and
touch-based samples of 29 subjects are captured in two different environmental
situations. Experiments on the acquired database show a comparable performance
of our touchless scheme and the touch-based baseline scheme under constrained
environmental influences. A comparative usability study on both capturing
device types indicates that the majority of subjects prefer the touchless
capturing method. Based on our experimental results we analyze the impact of
the current COVID-19 pandemic on fingerprint recognition systems. Finally,
implementation aspects of touchless fingerprint recognition are summarized.
