用虹膜识别技术为4-6周婴儿建立精准身份标识，防止新生儿错抱。
Iris Recognition for Infants
- 设计专用近红外传感器采集婴儿虹膜图像，提出新分割模型提取纹理特征。
- 系统在17名婴儿上实现3%错误率和99%识别准确率，远超成人水平。
- 开源合成婴儿虹膜数据集，保护隐私同时支持研究复现。
无创、高效、无需物理凭证的精准稳定新生儿识别方法，可预防出生时婴儿错抱、减少拐卖风险，并提升跨区域产后健康监测能力，适用于医院及人道主义脆弱环境。本文探索将虹膜识别应用于4-6周龄婴儿的可行性：（a）使用专用近红外（NIR）传感器采集17名婴儿的虹膜图像；（b）评估六种虹膜识别方法，检验现有技术对新生儿的适用性；（c）提出一种新型分割模型，准确检测婴儿虹膜纹理，并结合多种编码方法，首次构建完整可运行的婴儿虹膜识别系统；（d）训练基于StyleGAN的模型，生成模拟婴儿虹膜图像，向研究社区提供隐私安全的数据资源。所提系统结合定制传感器与分割模块，在采集的婴儿虹膜样本上实现等错误率（EER）3%、ROC曲线下面积（AUC）99%，显著优于现有成人虹膜系统（EER≥20%，AUC≤88%），表明从婴儿虹膜中成功提取生物特征具有可行性。
原文摘要 · Abstract (English)
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$\geq$20\% and AUC$\leq$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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。