Open Source Iris Recognition Hardware and Software with Presentation Attack Detection

TL;DR

This paper introduces an open source, low-cost iris recognition system with presentation attack detection, designed for easy assembly and educational use, utilizing Raspberry Pi and lightweight algorithms.

Contribution

It presents the first open source hardware and software iris recognition system with integrated presentation attack detection, suitable for low-cost and educational applications.

Findings

Recognition runs in about 3.2 seconds on Raspberry Pi 3B+

PAD runs in about 4.5 seconds on Raspberry Pi 3B+

All source code and hardware specifications are publicly available.

Abstract

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.