Digital Fingerprint Classification using data analytics algorithm: based on friction ridge characteristics withth KNN and Random Forest Algorithms

Digital Fingerprint Classification using data analytics algorithm: based on friction ridge characteristics withth KNN and Random Forest Algorithms | 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 Digital Fingerprint Classification using data analytics algorithm: based on friction ridge characteristics withth KNN and Random Forest Algorithms Satchithanantham. U, Karthikeyan. Kishore This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2743660/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 Fingerprint recognition is one of the most reliable and widely used biometric techniques for personal identification. The uniqueness and persistence of friction ridge patterns make fingerprints an ideal choice for forensic investigation and identification. In recent years, the advent of data analytics and machine learning algorithms has revolutionized the field of fingerprint recognition. In this paper, we propose a fingerprint digital classification system based on friction ridge characteristics and data analytics algorithms. We have used an open-source dataset of fingerprint images to test the proposed system. The results demonstrate the effectiveness and accuracy of the proposed approach. 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-2743660","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":187212830,"identity":"f2f31f74-3249-4840-a1e7-0eeb5ffa0cd4","order_by":0,"name":"Satchithanantham. 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