Fully Automated Unsupervised Learning Approach for Thermal Camera Calibration and An Accurate Human Temperature Tracking 

Fully Automated Unsupervised Learning Approach for Thermal Camera Calibration and An Accurate Human Temperature Tracking | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fully Automated Unsupervised Learning Approach for Thermal Camera Calibration and An Accurate Human Temperature Tracking Adil Al-Azzawi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4467631/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract During the past three years, people have suffered a lot from what the World Health Organization called the emerging Covid-19. The world lacked the means and methods for early detection of this virus, several methods were used traditional methods for detecting this virus, such as thermometers, a remote thermal detection gun, and other traditional methods. Most of these systems monopolized making profits or selling their camera products, as the prices of these cameras equipped with a temperature detection system exceeded three thousand dollars. An unsupervised model for real-time detection of thermal face skin temperature was proposed, despite the scarcity and availability of thermal video data, we found and used a database created at Nazarbayev University in Nur-Sultan, Kazakhstan, which contains clips of thermal video and RGB video. Where the two different videos were calibrated, and the congruence was measured by two measures, SSIM and Correlation, and then four methods of registration were used to achieve perfect congruence, and the congruence was also measured through the two previous measures, and then the K-means method was used to extract clusters, and then functions for post-processing were built, then, the thermal face skin was extracted by multiplying the binary face into the thermal face, and the temperature of the face was calculated by taking the average values of the thermal face skin pixels and converting them from Fahrenheit to Celsius. Satisfactory results were obtained for us, as temperatures were detected for some cases within the normal range, others below the normal range, and others higher than this rate. camera calibration unsupervised learning human temperature k-means clustering COVID-19 thermal camera Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4467631","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":309393036,"identity":"0308da21-6af8-4423-94b1-b25be873cf0d","order_by":0,"name":"Adil Al-Azzawi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYFCCxMYDDAwHeBgOMDA+YGCQSAAKGYARHi0NMC3MBkRqSWAAaQEhNgkwl4B6Bv72ZKAtv+7I8B0/e6ziZ5tFHgN78zYJhgJrnFokzjxsOMDY94xH8kxe2s3eNoliBp5jZRIMBum4rbkB9Atjz2EegwM5Zjd42yQSGyRyzIBaDuPUIQ/Xcv6NWeFfkBb5N/i1GIC0MPwAarmRY8YMsYUHvxZDkF8SGw7zSN54Yywtc06imI0nrdgiAY9f5I6nP3zw4c9he77zOYYf35TV5fGzH95448Mf3CEGBoltSBw2EJHAwIxfC8MfTCFCWkbBKBgFo2AEAQDyUFxO8KgFXAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Diyala","correspondingAuthor":true,"prefix":"","firstName":"Adil","middleName":"","lastName":"Al-Azzawi","suffix":""}],"badges":[],"createdAt":"2024-05-23 14:46:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4467631/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4467631/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58894356,"identity":"500347e6-5279-4203-9ac7-eb8b42b67f41","added_by":"auto","created_at":"2024-06-23 15:52:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1905986,"visible":true,"origin":"","legend":"","description":"","filename":"FullyAutomatedUnsupervisedLearningApproachforThermalCameraCalibrationandAnAccurateHumanTemperatureTrackingV6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4467631/v1_covered_7373c193-ff4a-4b3e-83da-608510d35e61.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":" Fully Automated Unsupervised Learning Approach for Thermal Camera Calibration and An Accurate Human Temperature Tracking ","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"camera calibration, unsupervised learning, human temperature, k-means, clustering, COVID-19, thermal camera","lastPublishedDoi":"10.21203/rs.3.rs-4467631/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4467631/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDuring the past three years, people have suffered a lot from what the World Health Organization called the emerging Covid-19. 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