A Reliable Technique for Currency Recognition Using Color and Texture Feature Extraction

A Reliable Technique for Currency Recognition Using Color and Texture Feature Extraction | 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 A Reliable Technique for Currency Recognition Using Color and Texture Feature Extraction Snehlata ., Vipin Saxena, Ashutosh Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3999655/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 Currency is the backbone of the Indian economy. Currency fraud is a serious offense that undermines a country’s financial stability. Because there are more counterfeit currencies on the market, India is dealing with a more serious issue. Currency identification has become a significant area of research nowadays. On November 8, 2016, the Indian government agencies announced the end of circulationof every single 500 and 1,000 rupee notes. There was also an introduction of ₹ 500 and ₹ 2,000 new currencies in exchange for demonetized currencies. After demonetization, there are many fake currencies came into the limelight. There are many fake currency detection approaches available as an alternative, but the majority of them are hardware-based and expensive. These security features are then encoded and fed into machine learning algorithms for feature detection and classification. A reliable approach for currency identification is formulated and also presents a framework for currency recognition based on the texture and color features of a currency, which applies to the Artificial Neural Network (ANN) model. The proposed work’s efficacy across various datasets is shown by experimental results, which also show that recognition performance can be achieved with a range of image sizes. Currency Image Processing Machine Learning Security Features Feature Extraction Counterfeit 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. 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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-3999655","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":275764149,"identity":"3c496d5b-3908-43ea-9642-ef55ba7a641b","order_by":0,"name":"Snehlata .","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBACPiA+AGIYMDAfOPAByGBjJ6CFDaGFLfHgDJAIMxFaGCBaeIwP84BYBLWwt188XPDnjpw5+xmDwza/tsnzMTMwfviYg0cLz5mCwzPbnhlb9qQVHM7tu23YxszALDlzGx4tEjkJh3kbDiduOJC84XBuz21GoBY2Zl5CWnj+HK7fcP6BwWHLntv2RGhJP3CYh+1wgsGNFIPDDD9uJxLWwnOG4TBv22HDDTeeJRzsbbid3MbM2IzXL/zs7Y8/Ax0mb3A++fCHH39u285vbz744SMeLQwMPAYINmMbmGzApx4I2B8gcf4QUDwKRsEoGAUjEgAABqNYqU0C9Q8AAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Snehlata","middleName":"","lastName":".","suffix":""},{"id":275764150,"identity":"7cb328ec-6576-4905-bc4a-a2a5ba8559fb","order_by":1,"name":"Vipin Saxena","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Vipin","middleName":"","lastName":"Saxena","suffix":""},{"id":275764151,"identity":"924b13d6-2f38-4cd9-9c6a-ee6b1f2fd9e2","order_by":2,"name":"Ashutosh Singh","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ashutosh","middleName":"","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2024-02-29 12:35:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3999655/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3999655/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52835265,"identity":"2f1f5e98-32be-4a75-9a13-4be9ba9b9c45","added_by":"auto","created_at":"2024-03-17 10:07:08","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2334854,"visible":true,"origin":"","legend":"","description":"","filename":"IJDA.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3999655/v1_covered_e9d40562-f468-4e01-804c-2443a0520720.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Reliable Technique for Currency Recognition Using Color and Texture Feature Extraction\u003c/p\u003e","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":"Currency, Image Processing, Machine Learning, Security Features, Feature Extraction, Counterfeit","lastPublishedDoi":"10.21203/rs.3.rs-3999655/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3999655/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCurrency is the backbone of the Indian economy. Currency fraud is a serious offense that undermines a country’s financial stability. Because there are more counterfeit currencies on the market, India is dealing with a more serious issue. Currency identification has become a significant area of research nowadays. On November 8, 2016, the Indian government agencies announced the end of circulationof every single 500 and 1,000 rupee notes. There was also an introduction of ₹ 500 and ₹ 2,000 new currencies in exchange for demonetized currencies. After demonetization, there are many fake currencies came into the limelight. There are many fake currency detection approaches available as an alternative, but the majority of them are hardware-based and expensive. These security features are then encoded and fed into machine learning algorithms for feature detection and classification. 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