A distorted QR code correction method based on heatmap regression

A distorted QR code correction method based on heatmap regression | 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 distorted QR code correction method based on heatmap regression Jiabao Zhang, Chenyao Luo, Yuheng Zha, Kexue Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7398424/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Oct, 2025 Read the published version in Signal, Image and Video Processing → Version 1 posted 5 You are reading this latest preprint version Abstract To address the issue of Quick Response Code (QR code) decoding failure caused by complex geometric distortions, such as surface attachment and folding deformation, this paper proposes a deep learning correction network based on heat map regression. The method dynamically adjusts the sensory field to adapt the distortion intensity through adaptive dilation convolution (ADConv) to preserve the geometric accuracy of the position detection pattern; designs the grouped CBAM enhancement module (GCE) to group the feature channels for parallel processing to strengthen the significant features of the boundary and key regions; transforms the coordinate prediction into probabilistic heatmap regression and combines with the sub pixel offset prediction to achieve the control point of the high precision The final reconstruction of the regular QR code image is performed by thin-plate spline transformation (TPS). Validation on a dataset containing 12,000 warped QR codes demonstrates that the scheme is successful in terms of PSNR (10.35 dB), SSIM (68.40%), and decode rate (91.4%). The correction scheme proposed in this paper is robust to the correction of severely deformed QR codes, such as large curvature distortion or folding, and provides reliable technical support for logistics traceability, mobile payment, industrial code reading, and other scenarios.Keywords:Distorted QR code; Adaptive dilation convolution; Grouped CBAM enhancement module; Heatmap regression; Thin plate spline transformation Distorted QR code Adaptive dilation convolution Grouped CBAM enhancement module Heatmap regression Thin plate spline transformation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Oct, 2025 Read the published version in Signal, Image and Video Processing → Version 1 posted Editorial decision: Revision requested 22 Aug, 2025 Reviewers invited by journal 22 Aug, 2025 Editor assigned by journal 19 Aug, 2025 Submission checks completed at journal 19 Aug, 2025 First submitted to journal 18 Aug, 2025 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-7398424","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503979707,"identity":"06689230-f7a8-4bd3-95b4-0f9641371b03","order_by":0,"name":"Jiabao Zhang","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Jiabao","middleName":"","lastName":"Zhang","suffix":""},{"id":503979708,"identity":"5c3303fb-0324-47ac-aec3-0122efe00860","order_by":1,"name":"Chenyao Luo","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Chenyao","middleName":"","lastName":"Luo","suffix":""},{"id":503979709,"identity":"035f8f3b-81df-4746-80f5-bd718ee06b54","order_by":2,"name":"Yuheng Zha","email":"","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Yuheng","middleName":"","lastName":"Zha","suffix":""},{"id":503979710,"identity":"625df689-ce6e-4d6e-924f-e518fde9e1b3","order_by":3,"name":"Kexue Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYHACZgaGChABAmxEazkDIphJ0cLYBtVKlBb5GbmHjXnn3WE3uN1/gOFD2WEG/tkN+LUY3MhLTpy57RmzwZ3DDIwzzh1mkLhzgIAWiRzjAx+3HWY2uJHMwMzbdhgokkDIYUAtiXOgWv4So4XhRo5xwscGqBZGYrQYnHljbDjj2GFmyTuHDQ72nEvnkbhByGHtOcbSPDWHk/luNz588KPMWo5/BiGHQUEygwQDwwEgg4c49UBgB9IyCkbBKBgFowArAAC0NUFkR4oBgAAAAABJRU5ErkJggg==","orcid":"","institution":"Nanjing University of Posts and Telecommunications","correspondingAuthor":true,"prefix":"","firstName":"Kexue","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2025-08-18 10:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7398424/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7398424/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11760-025-04915-w","type":"published","date":"2025-10-29T15:57:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":95040435,"identity":"b3c47475-995f-42c2-9df0-3d2cc158984f","added_by":"auto","created_at":"2025-11-03 16:08:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":23001342,"visible":true,"origin":"","legend":"","description":"","filename":"AdistortedQRcodecorrectionmethodbasedonheatmapregression.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7398424/v1_covered_62691f16-fb05-48cc-b2f8-408893e032e0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A distorted QR code correction method based on heatmap regression","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Distorted QR code, Adaptive dilation convolution, Grouped CBAM enhancement module, Heatmap regression, Thin plate spline transformation","lastPublishedDoi":"10.21203/rs.3.rs-7398424/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7398424/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"To address the issue of Quick Response Code (QR code) decoding failure caused by complex geometric distortions, such as surface attachment and folding deformation, this paper proposes a deep learning correction network based on heat map regression. 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