<!doctype html><html lang="en" class="no-js"><head><meta charset="utf-8"> <!-- begin SEO --><title>Human and machine performance on periocular biometrics under near-infrared light and visible light - S. Solomon Darnell’s Research</title><meta name="description" content="Periocular biometrics is the recognition of individuals based on the appearance of the region around the eye. Periocular recognition may be useful in applications where it is difficult to obtain a clear picture of an iris for iris biometrics, or a complete picture of a face for face biometrics. Previous periocular research has used either visible-light (VL) or near-infrared (NIR) light images, but no prior research has directly compared the two illuminations using images with similar resolution. We conducted an experiment in which volunteers were asked to compare pairs of periocular images. Some pairs showed images taken in VL, and some showed images taken in NIR light. Participants labeled each pair as belonging to the same person or to different people. Untrained participants with limited viewing times correctly classified VL image pairs with 88% accuracy, and NIR image pairs with 79% accuracy. For comparison, we presented pairs of iris images from the same subjects. In addition, we investigated differences between performance on light and dark eyes and relative helpfulness of various features in the periocular region under different illuminations. We calculated performance of three computer algorithms on the periocular images. Performance for humans and computers was similar."><meta property="article:published_time" content="2012-04-02T00:00:00+00:00"><link rel="canonical" href="https://shelbysolomondarnell.github.io/publication/2012-04-02-ieee-periocular.md"> <script type="application/ld+json"> { "@context" : "http://schema.org", "@type" : "Person", "name" : "S. Solomon Darnell", "url" : "https://shelbysolomondarnell.github.io", "sameAs" : null } </script> <!-- end SEO --> <!-- Open Graph protocol data (https://ogp.me/), used by social media --><meta property="og:locale" content="en-US"><meta property="og:site_name" content="S. Solomon Darnell's Research"><meta property="og:title" content="Human and machine performance on periocular biometrics under near-infrared light and visible light"><meta property="og:type" content="article"><meta property="og:description" name="description" content="Periocular biometrics is the recognition of individuals based on the appearance of the region around the eye. Periocular recognition may be useful in applications where it is difficult to obtain a clear picture of an iris for iris biometrics, or a complete picture of a face for face biometrics. Previous periocular research has used either visible-light (VL) or near-infrared (NIR) light images, but no prior research has directly compared the two illuminations using images with similar resolution. We conducted an experiment in which volunteers were asked to compare pairs of periocular images. Some pairs showed images taken in VL, and some showed images taken in NIR light. Participants labeled each pair as belonging to the same person or to different people. Untrained participants with limited viewing times correctly classified VL image pairs with 88% accuracy, and NIR image pairs with 79% accuracy. For comparison, we presented pairs of iris images from the same subjects. In addition, we investigated differences between performance on light and dark eyes and relative helpfulness of various features in the periocular region under different illuminations. We calculated performance of three computer algorithms on the periocular images. Performance for humans and computers was similar."><meta property="og:url" content="https://shelbysolomondarnell.github.io/publication/2012-04-02-ieee-periocular.md"> <!-- end Open Graph protocol --><link href="https://shelbysolomondarnell.github.io/feed.xml" type="application/atom+xml" rel="alternate" title="S. Solomon Darnell's Research Feed"><meta name="viewport" content="width=device-width, initial-scale=1.0"> <script> document.documentElement.className = document.documentElement.className.replace(/\bno-js\b/g, '') + ' js '; </script> <!-- For all browsers --><link rel="stylesheet" href="https://shelbysolomondarnell.github.io/assets/css/main.css"> <!-- start custom head snippets --> <!-- Support for Academicons --><link rel="stylesheet" href="https://shelbysolomondarnell.github.io/assets/css/academicons.css"/> <!-- favicon from https://commons.wikimedia.org/wiki/File:OOjs_UI_icon_academic-progressive.svg --><link rel="apple-touch-icon" sizes="180x180" href="https://shelbysolomondarnell.github.io/images/apple-touch-icon-180x180.png"/><link rel="icon" type="image/svg+xml" href="https://shelbysolomondarnell.github.io/images/favicon.svg"/><link rel="icon" type="image/png" href="https://shelbysolomondarnell.github.io/images/favicon-32x32.png" sizes="32x32"/><link rel="icon" type="image/png" href="https://shelbysolomondarnell.github.io/images/favicon-192x192.png" sizes="192x192"/><link rel="manifest" href="https://shelbysolomondarnell.github.io/images/manifest.json"/><link rel="icon" href="/images/favicon.ico"/><meta name="theme-color" content="#ffffff"/> <!-- end custom head snippets --></head><body> <!--[if lt IE 9]><div class="notice--danger align-center" style="margin: 0;">You are using an <strong>outdated</strong> browser. Please <a href="http://browsehappy.com/">upgrade your browser</a> to improve your experience.</div><![endif]--><div class="masthead"><div class="masthead__inner-wrap"><div class="masthead__menu"><nav id="site-nav" class="greedy-nav"> <button><span class="navicon"></span></button><ul class="visible-links"><li class="masthead__menu-item masthead__menu-item--lg persist "> <a href="https://shelbysolomondarnell.github.io/">S. Solomon Darnell's Research</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/publications/">Publications</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/talks/">Talks</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/teaching/">Teaching</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/portfolio/">Portfolio</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/year-archive/">Blog Posts</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/cv/">CV</a></li><li class="masthead__menu-item "> <a href="https://shelbysolomondarnell.github.io/markdown/">Guide</a></li><li id="theme-toggle" class="masthead__menu-item persist tail"> <a role="button" aria-labelledby="theme-icon"><i id="theme-icon" class="fa-solid fa-sun" aria-hidden="true" title="toggle theme"></i></a></li></ul><ul class="hidden-links hidden"></ul></nav></div></div></div><nav class="breadcrumbs"><ol itemscope itemtype="http://schema.org/BreadcrumbList"><li itemprop="itemListElement" itemscope itemtype="http://schema.org/ListItem"> <a href="https://shelbysolomondarnell.github.io/" itemprop="item"><span itemprop="name">Home</span></a><meta itemprop="position" content="1" /></li><span class="sep">/</span><li itemprop="itemListElement" itemscope itemtype="http://schema.org/ListItem"> <a href="https://shelbysolomondarnell.github.io/publication" itemprop="item"><span itemprop="name">Publication</span></a><meta itemprop="position" content="2" /></li><span class="sep">/</span><li class="current">Human and machine performance on periocular biometrics under near-infrared light and visible light</li></ol></nav><div id="main" role="main"><div class="sidebar sticky"><div itemscope itemtype="http://schema.org/Person"><div class="author__avatar"> <img src="https://shelbysolomondarnell.github.io/images/profile.png" class="author__avatar" alt="SSD" fetchpriority="high" /></div><div class="author__content"><h3 class="author__name">SSD</h3><p class="author__pronouns"></p><p class="author__bio">Adaptive Researcher</p></div><div class="author__urls-wrapper"> <button class="btn btn--inverse">Follow</button><ul class="author__urls social-icons"> <!-- Font Awesome icons / Biographic information --><li class="author__desktop"><i class="fas fa-fw fa-location-dot icon-pad-right" aria-hidden="true"></i></li><li class="author__desktop"><i class="fas fa-fw fa-building-columns icon-pad-right" aria-hidden="true"></i>Nyeusi Technology</li><li><a href="mailto:learner@nyeusi.tech"><i class="fas fa-fw fa-envelope icon-pad-right" aria-hidden="true"></i>Email</a></li><!-- Font Awesome and Academicons icons / Academic websites --><li><a href="https://scholar.google.com/citations?user=UgQjoGsAAAAJ"><i class="ai ai-google-scholar ai-fw icon-pad-right"></i>Google Scholar</a></li><li><a href="https://orcid.org/0000-0002-4841-4398"><i class="ai ai-orcid ai-fw icon-pad-right"></i>ORCID</a></li><li><a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=darnell+ss"><i class="ai ai-pubmed ai-fw icon-pad-right"></i>PubMed</a></li><!-- Font Awesome icons / Repositories and software development --><li><a href="https://github.com/shelbysolomondarnell"><i class="fab fa-fw fa-github icon-pad-right" aria-hidden="true"></i>GitHub</a></li><!-- Font Awesome icons / Social media --><li><a href="https://bsky.app/profile/"><i class="fab fa-fw fa-bluesky icon-pad-right" aria-hidden="true"></i>Bluesky</a></li></ul></div></div></div><article class="page" itemscope itemtype="http://schema.org/CreativeWork"><meta itemprop="headline" content="Human and machine performance on periocular biometrics under near-infrared light and visible light"><meta itemprop="description" content="Periocular biometrics is the recognition of individuals based on the appearance of the region around the eye. Periocular recognition may be useful in applications where it is difficult to obtain a clear picture of an iris for iris biometrics, or a complete picture of a face for face biometrics. Previous periocular research has used either visible-light (VL) or near-infrared (NIR) light images, but no prior research has directly compared the two illuminations using images with similar resolution. We conducted an experiment in which volunteers were asked to compare pairs of periocular images. Some pairs showed images taken in VL, and some showed images taken in NIR light. Participants labeled each pair as belonging to the same person or to different people. Untrained participants with limited viewing times correctly classified VL image pairs with 88% accuracy, and NIR image pairs with 79% accuracy. For comparison, we presented pairs of iris images from the same subjects. In addition, we investigated differences between performance on light and dark eyes and relative helpfulness of various features in the periocular region under different illuminations. We calculated performance of three computer algorithms on the periocular images. Performance for humans and computers was similar."><meta itemprop="datePublished" content="April 02, 2012"><div class="page__inner-wrap"><header><h1 class="page__title" itemprop="headline">Human and machine performance on periocular biometrics under near-infrared light and visible light</h1><p>Published in <i>IEEE Transactions on Information Forensics and Security</i>, 2012</p></header><section class="page__content" itemprop="text"><p>The contents above will be part of a list of publications, if the user clicks the link for the publication than the contents of section will be rendered as a full page, allowing you to provide more information about the paper for the reader. When publications are displayed as a single page, the contents of the above “citation” field will automatically be included below this section in a smaller font.</p><p style="font-size: smaller">Recommended citation: <br /><a href="https://ieeexplore.ieee.org/abstract/document/6062410/">Download Paper</a> | <a href="">Download Slides</a> | <a href="">Download Bibtex</a></p></section><footer class="page__meta"></footer><section class="page__share"><h4 class="page__share-title">Share on</h4><a href="https://bsky.app/intent/compose?text=https://shelbysolomondarnell.github.io/publication/2012-04-02-ieee-periocular.md" class="btn btn--bluesky" title="Share on Bluesky"><i class="fab fa-bluesky" aria-hidden="true"></i><span> Bluesky</span></a> <a href="https://www.facebook.com/sharer/sharer.php?u=https://shelbysolomondarnell.github.io/publication/2012-04-02-ieee-periocular.md" class="btn btn--facebook" title="Share on Facebook"><i class="fab fa-facebook" aria-hidden="true"></i><span> Facebook</span></a> <a href="https://www.linkedin.com/shareArticle?mini=true&url=https://shelbysolomondarnell.github.io/publication/2012-04-02-ieee-periocular.md" class="btn btn--linkedin" title="Share on LinkedIn"><i class="fab fa-linkedin" aria-hidden="true"></i><span> LinkedIn</span></a> <a href="https://www.addtoany.com/add_to/mastodon?linkurl=https%3A%2F%2Fshelbysolomondarnell.github.io%2Fpublication%2F2012-04-02-ieee-periocular.md" class="btn btn--mastodon" title="Share on Mastodon"><i class="fab fa-mastodon" aria-hidden="true"></i><span> Mastodon</span></a> <a href="https://x.com/intent/post?text=https://shelbysolomondarnell.github.io/publication/2012-04-02-ieee-periocular.md" class="btn btn--x" title="Share on X"><i class="fab fa-x-twitter" aria-hidden="true"></i><span> X (formerly Twitter)</span></a></section><nav class="pagination"> <a href="https://shelbysolomondarnell.github.io/publication/" class="pagination--pager" title="Locus of control in coversational agent design: Effects on older users’ interactivity and social presence ">Previous</a> <a href="https://shelbysolomondarnell.github.io/publication/2013-01-01-dapi-privacytrust" class="pagination--pager" title="Understanding Privacy and Trust Isues in a Classroom Affective Computing System Deployment ">Next</a></nav></div></article></div><div class="page__footer"><footer> <!-- start custom footer snippets --> <a href="/sitemap/">Sitemap</a> <!-- Support for MatJax --> <script defer src="https://cdnjs.cloudflare.com/polyfill/v3/polyfill.min.js?features=es6"></script> <script defer src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js" id="MathJax-script"></script> <!-- Support for Mermaid --> <script type="module"> import mermaid from 'https://cdn.jsdelivr.net/npm/mermaid@11/dist/mermaid.esm.min.mjs'; mermaid.initialize({startOnLoad:true, theme:'default'}); await mermaid.run({querySelector:'code.language-mermaid'}); </script> <!-- end custom footer snippets --><div class="page__footer-follow"><ul class="social-icons"><li><strong>Follow:</strong></li><li><a href="https://github.com/shelbysolomondarnell"><i class="fab fa-github" aria-hidden="true"></i> GitHub</a></li><li><a href="https://shelbysolomondarnell.github.io/feed.xml"><i class="fa fa-fw fa-rss-square" aria-hidden="true"></i> Feed</a></li></ul></div><div class="page__footer-copyright"> &copy; 2026 S. Solomon Darnell, Powered by <a href="https://jekyllrb.com" rel="nofollow">Jekyll</a> &amp; <a href="https://github.com/academicpages/academicpages.github.io">AcademicPages</a>, a fork of <a href="https://mademistakes.com/work/minimal-mistakes-jekyll-theme/" rel="nofollow">Minimal Mistakes</a>.<br /> Site last updated 2026-04-05</div></footer></div><script type="module" src="https://shelbysolomondarnell.github.io/assets/js/main.min.js"></script></body></html>
