# Iris Recognition for Infants

arXiv: https://arxiv.org/abs/2501.01375 · HTML: https://mlsanity.com/paper/2501.01375/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 51 references that are in the map.
- First posted on arXiv 2 Jan 2025.

## Builds on (most cited first, 10 of 10)

- [Graph Attention Networks](https://mlsanity.com/paper/1710.10903/) (2017)
- [Training Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2006.06676/) (2020)
- [Post-mortem Iris Recognition with Deep-Learning-based Image Segmentation](https://mlsanity.com/paper/1901.01708/) (2019)
- [OpenEDS: Open Eye Dataset](https://mlsanity.com/paper/1905.03702/) (2019)
- [Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition](https://mlsanity.com/paper/1807.05248/) (2018)
- [Iris Recognition After Death](https://mlsanity.com/paper/1804.01962/) (2018)
- [Human Iris Recognition in Post-mortem Subjects: Study and Database](https://mlsanity.com/paper/1809.00174/) (2018)
- [Iris Recognition Performance in Children: A Longitudinal Study](https://mlsanity.com/paper/2101.06346/) (2021)
- [Two-headed eye-segmentation approach for biometric identification](https://mlsanity.com/paper/2209.15471/) (2022)
- [Linear regression analysis of template aging in iris biometrics](https://mlsanity.com/paper/1809.00170/) (2018)

## Built on by (most cited first, 2 of 2)

- [Synthetic Iris Image Databases and Identity Leakage: Risks and Mitigation Strategies](https://mlsanity.com/paper/2506.02626/) (2025)
- [Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognition](https://mlsanity.com/paper/2605.20735/) (2026)

## Abstract (arXiv)

Non-invasive, efficient, physical token-less, accurate and stable identification methods for newborns may prevent baby swapping at birth, limit baby abductions and improve post-natal health monitoring across geographies, within the context of both the formal (i.e., hospitals) and informal (i.e., humanitarian and fragile settings) health sectors. This paper explores the feasibility of application iris recognition to build biometric identifiers for 4-6 week old infants. We (a) collected near infrared (NIR) iris images from 17 infants using a specially-designed NIR iris sensor; (b) evaluated six iris recognition methods to assess readiness of the state-of-the-art iris recognition to be applied to newborns and infants; (c) proposed a new segmentation model that correctly detects iris texture within infants iris images, and coupled it with several iris texture encoding approaches to offer, to the first of our knowledge, a fully-operational infant iris recognition system; and, (d) trained a StyleGAN-based model to synthesize iris images mimicking samples acquired from infants to deliver to the research community privacy-safe infant iris images. The proposed system, incorporating the specially-designed iris sensor and segmenter, and applied to the collected infant iris samples, achieved Equal Error Rate (EER) of 3% and Area Under ROC Curve (AUC) of 99%, compared to EER≥20% and AUC≤88% obtained for state of the art adult iris recognition systems. This suggests that it may be feasible to design methods that succesfully extract biometric features from infant irises.