  This paper proposes the first known to us open source hardware and software
iris recognition system with presentation attack detection (PAD), which can be
easily assembled for about 75 USD using Raspberry Pi board and a few
peripherals. The primary goal of this work is to offer a low-cost baseline for
spoof-resistant iris recognition, which may (a) stimulate research in iris PAD
and allow for easy prototyping of secure iris recognition systems, (b) offer a
low-cost secure iris recognition alternative to more sophisticated systems, and
(c) serve as an educational platform. We propose a lightweight image
complexity-guided convolutional network for fast and accurate iris
segmentation, domain-specific human-inspired Binarized Statistical Image
Features (BSIF) to build an iris template, and to combine 2D (iris texture) and
3D (photometric stereo-based) features for PAD. The proposed iris recognition
runs in about 3.2 seconds and the proposed PAD runs in about 4.5 seconds on
Raspberry Pi 3B+. The hardware specifications and all source codes of the
entire pipeline are made available along with this paper.
