Rail Image Harmonization Dataset: A Seed to Generate Evaluation Resources for Track Vision Inspection Systems

Rail Image Harmonization Dataset: A Seed to Generate Evaluation Resources for Track Vision Inspection Systems | 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 Rail Image Harmonization Dataset: A Seed to Generate Evaluation Resources for Track Vision Inspection Systems Yu He, Zishen Zhao, Zhi Han, Chunlei Chen, Jinfei Hao, Qiang Fu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8130209/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract The track visual inspection system is a critical component in maintaining railway transportation safety. The scarcity of abnormal rail images presents a significant challenge for evaluating the performance of such inspection systems across diverse local railway divisions. Image harmonization emerges as a pivotal technique for generating evaluation resources for track vision inspection systems. However, the lack of suitable datasets has resulted in limited reporting on rail image harmonization techniques. This paper introduces the first Rail Image Harmonization Dataset (RHD). The dataset comprises 218 high-resolution rail images containing abnormal fasteners, captured by two inspection vehicles, and provides 14,712 pairs of inharmonious and harmonized rail image samples. Extensive experiments utilizing RHD were conducted, evaluating existing high-resolution harmonization methods alongside a specialized method termed Rail-DCCF -- a simplification of the state-of-the-art DCCF method. Comprehensive analyses of the RHD and the harmonization techniques employed in these methods are presented. RHD will provide fundamental data support for the research of rail image harmonization. Terms– Dataset image harmonization railway track inspection fastener Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Mar, 2026 Reviews received at journal 05 Mar, 2026 Reviewers agreed at journal 05 Mar, 2026 Reviews received at journal 09 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviewers agreed at journal 06 Feb, 2026 Reviewers invited by journal 19 Jan, 2026 Editor assigned by journal 17 Dec, 2025 Submission checks completed at journal 18 Nov, 2025 First submitted to journal 16 Nov, 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. 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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-8130209","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":576770087,"identity":"86cf7361-c832-41e9-b7f4-42075dfbe4a5","order_by":0,"name":"Yu He","email":"","orcid":"","institution":"China Academy of Railway Sciences Corporation Limited","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"He","suffix":""},{"id":576770091,"identity":"be026e50-9704-4b3d-b32f-2eab5babb38c","order_by":1,"name":"Zishen Zhao","email":"","orcid":"","institution":"China Academy of Railway Sciences Corporation 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