Enhanced Rock Fracture Detection: Integrating DeepLabv3+ Segmentation with Geometric Pattern Analysis

Enhanced Rock Fracture Detection: Integrating DeepLabv3+ Segmentation with Geometric Pattern Analysis | 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 Enhanced Rock Fracture Detection: Integrating DeepLabv3+ Segmentation with Geometric Pattern Analysis Qiancheng Tan, Yonghui Qin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9160848/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 Rock mass fracture identification plays a pivotal role in geological analysis and underground engineering. Accurate extraction of fracture structures from complex rock images remains challenging due to irregular morphologies and background interferences. This study introduces a framework that integrates DeepLabv3+- based semantic segmentation with geometric pattern modeling to address these challenges. The framework employs multi-scale convolutional networks and attention mechanisms to enhance feature extraction accuracy. Subsequently, trigonometric scatter point pattern modeling is utilized to characterize fracture orientation and continuity. Experimental results demonstrate that our approach achieves superior accuracy and robustness, with a 10% improvement in Dice coefficient compared to existing methods, highlighting its effectiveness for precise rock mass fracture identification. Rock mass fracture identification Semantic segmentation DeepLabv3+ Scatter point modeling Trigonometric pattern analysis Full Text Additional Declarations The authors declare no competing interests. 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-9160848","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":608359922,"identity":"49759810-9c40-456d-ba7c-eae3ae6eb93b","order_by":0,"name":"Qiancheng Tan","email":"","orcid":"https://orcid.org/0009-0007-7727-8640","institution":"Guilin University of Electronic Technology","correspondingAuthor":false,"prefix":"","firstName":"Qiancheng","middleName":"","lastName":"Tan","suffix":""},{"id":608359923,"identity":"a53b0668-329e-4065-b872-72b1c6b4e702","order_by":1,"name":"Yonghui Qin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYJACZgYGCR5++ccHHyRU1BCvRUayIS3Z4MGZY0RrYbAxaMhRk3zYwkxYucHx3sOvC9sseAwYzrBVJDawMfC3dyfg13LmXJr1zDYJHnPG3mM3EnfIMEicObsBv5YbOWbGvEAtls18aTcSz7AxGEjkEqnF4BiPWUFiGzNRWowfg7Wc4TFjIEqL5JkzZsw85yR4JGewJUsknDnGQ9AvfMd7jD/zlNXZ80swH/z4o6JGjr+9F78WhQMMbBLIAjx4lYOAfAMD8weCqkbBKBgFo2BkAwAmX0aC/he6QgAAAABJRU5ErkJggg==","orcid":"","institution":"Guilin University of Electronic Technology","correspondingAuthor":true,"prefix":"","firstName":"Yonghui","middleName":"","lastName":"Qin","suffix":""}],"badges":[],"createdAt":"2026-03-18 15:04:45","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9160848/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9160848/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104965331,"identity":"45564af8-cdfe-46c6-a706-d2975fd0321e","added_by":"auto","created_at":"2026-03-19 09:41:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":18286145,"visible":true,"origin":"","legend":"","description":"","filename":"RockFractureDeepLabv3Pattern.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9160848/v1_covered_8aed3281-d2dd-4a30-a8d7-a45818115616.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eEnhanced Rock Fracture Detection: Integrating DeepLabv3+ Segmentation with Geometric Pattern Analysis\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[{"identity":"ca51fead-0eff-4ed6-90d0-a343b6f79c93","identifier":"10.13039/501100001809","name":"National Natural Science Foundation of China","awardNumber":"No. 12561067 and 12161025","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Guilin University of Electronic Technology","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"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":"Rock mass fracture identification, Semantic segmentation, DeepLabv3+, Scatter point modeling, Trigonometric pattern analysis","lastPublishedDoi":"10.21203/rs.3.rs-9160848/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9160848/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRock mass fracture identification plays a pivotal role in geological analysis and underground engineering. 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