  This work presents the first survey on fingerprint pore detection. The survey
provides a general overview of the field and discusses methods, datasets, and
evaluation protocols. We also present a baseline method inspired on the
state-of-the-art that implements a customizable Fully Convolutional Network,
whose hyperparameters were tuned to achieve optimal pore detection rates.
Finally, we also reimplementated three other approaches proposed in the
literature for evaluation purposes. We have made the source code of (1) the
baseline method, (2) the reimplemented approaches, and (3) the training and
evaluation processes for two different datasets available to the public to
attract more researchers to the field and to facilitate future comparisons
under the same conditions. The code is available in the following repository:
https://github.com/azimIbragimov/Fingerprint-Pore-Detection-A-Survey
