A Mask-Fusion Detection Method for Character Integrity Preservation and Adhesion Segmentation in Jiandu Manuscripts

A Mask-Fusion Detection Method for Character Integrity Preservation and Adhesion Segmentation in Jiandu Manuscripts | 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 Article A Mask-Fusion Detection Method for Character Integrity Preservation and Adhesion Segmentation in Jiandu Manuscripts Yingwei Hong, Cheng Hua, Yujie Guo, Zhaoyu Huang, Hongbo He, Hongxi Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8970025/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Jiandu served as the primary medium for recording important information in ancient China, and the analysis and interpretation of their textual content contribute to a deeper understanding of history and the preservation of cultural heritage. Jiandu text detection is a prerequisite for subsequent text recognition and semantic analysis. To address challenges such as surface aging, irregular character scales, dense character arrangement, and intersecting character adhesion in Jiandu images, this paper proposes a Jiandu text detection method based on character-level region mask fusion and adaptive segmentation, aiming to better preserve character structures and effectively segment adhered characters. In the automatic segmentation stage, a pixel feature analysis and overlap suppression mechanism is introduced to reduce background noise and invalid regions. In the character region processing stage, mask clustering and region fusion strategies are employed to alleviate the effects of inter-character occlusion and adhesion. Subsequently, an adaptive segmentation method is applied to achieve accurate segmentation of individual characters from complex adhered character regions. Experimental results demonstrate that the proposed method achieves significant improvements in character structure preservation and adhered character segmentation, effectively enhancing the overall performance of Jiandu text detection. Jiandu text detection character adhesion segmentation mask segmentation region mask fusion Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 18 Mar, 2026 Reviews received at journal 17 Mar, 2026 Reviews received at journal 13 Mar, 2026 Reviewers agreed at journal 08 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers invited by journal 02 Mar, 2026 Editor assigned by journal 02 Mar, 2026 Submission checks completed at journal 02 Mar, 2026 First submitted to journal 25 Feb, 2026 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. 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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-8970025","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":600279768,"identity":"c6330ba8-9db7-4dbd-81fe-2e118d8abd8f","order_by":0,"name":"Yingwei 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