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This paper proposes the first known to us open source hardware and softwareiris recognition system with presentation attack detection (PAD), which can beeasily assembled for about 75 USD using Raspberry Pi board and a fewperipherals. The primary goal of this work is to offer a low-cost baseline forspoof-resistant iris recognition, which may (a) stimulate research in iris PADand allow for easy prototyping of secure iris recognition systems, (b) offer alow-cost secure iris recognition alternative to more sophisticated systems, and(c) serve as an educational platform. We propose a lightweight imagecomplexity-guided convolutional network for fast and accurate irissegmentation, domain-specific human-inspired Binarized Statistical ImageFeatures (BSIF) to build an iris template, and to combine 2D (iris texture) and3D (photometric stereo-based) features for PAD. The proposed iris recognitionruns in about 3.2 seconds and the proposed PAD runs in about 4.5 seconds onRaspberry Pi 3B+. The hardware specifications and all source codes of theentire pipeline are made available along with this paper.

Open Source Iris Recognition Hardware and Software with Presentation Attack Detection