An exponential intensity mapping method for grayscale drift suppression in high-temperature forging images

An exponential intensity mapping method for grayscale drift suppression in high-temperature forging images | 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 An exponential intensity mapping method for grayscale drift suppression in high-temperature forging images Liqun Niu, Zike Li, Xuming Wang, Bingzheng Wang, Zhenglong Liang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8753559/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 High-temperature forging images often suffer from non-stationary grayscale drift caused by the formation and spallation of oxide scale. This drift degrades the robustness of fixed-threshold Canny edge detection and similarity-based region growing segmentation. To address this issue, an exponential intensity mapping preprocessing method is proposed that suppresses grayscale drift by selectively enhancing the high-intensity forging region while attenuating the low-intensity background, thereby increasing foreground-background separability. The mapping parameters are calibrated on representative production images using a two-point anchoring strategy: stable foreground and background intensity anchors are estimated from quantiles, and the gain and offset are solved analytically under a fixed enhancement strength. Experiments on 79 manually annotated images show that the median region-growing coverage improves from 4.26×10−4 to 0.9438, with the 90th percentile reaching 0.9912. For contour extraction, the band-limited Boundary F1 of Canny increases from 0.7117 to 0.7740. These results demonstrate that the proposed preprocessing effectively compensates for oxide-scale-induced grayscale drift and improves the stability of contour extraction and segmentation without modifying downstream algorithms or adding hardware. high-temperature forging image preprocessing Canny region growing machine vision 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. 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-8753559","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583753297,"identity":"3901651f-2a66-410e-939b-dbb98f3753a8","order_by":0,"name":"Liqun Niu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYDACZgbGAwlAmo2ZsfFBQoUNUVoYwFr42JmbDR6cSSPOogMgQo6fvU3yYdshwsrN2XkMDjwoO5wHdFhbRQLbAQb+9u4EvFosm4FaEs4dLgZpuZHAc4dB4szZDXi1GBwGaklsO5zYBtYi8YzBQCKXBC0FCQaHSdTCkJBAlBa2AqBf0kFamiUSDqTxEPbL+cMbH/4os06c33/84cef/2zk+Nt78WuBADYEk4cI5WhaRsEoGAWjYBRgAAC3KktemRBPjQAAAABJRU5ErkJggg==","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Liqun","middleName":"","lastName":"Niu","suffix":""},{"id":583753299,"identity":"05c29657-b967-4684-b670-3fa7af664c0a","order_by":1,"name":"Zike Li","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Zike","middleName":"","lastName":"Li","suffix":""},{"id":583753304,"identity":"0edf4124-0a90-4dc7-9110-aaeccdd6172b","order_by":2,"name":"Xuming Wang","email":"","orcid":"","institution":"Lanzhou Lanshi Super Alloy New Material Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Xuming","middleName":"","lastName":"Wang","suffix":""},{"id":583753307,"identity":"1870f36d-c451-467e-b2f6-530873404b49","order_by":3,"name":"Bingzheng Wang","email":"","orcid":"","institution":"Lanzhou Lanshi Super Alloy New Material Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Bingzheng","middleName":"","lastName":"Wang","suffix":""},{"id":583753308,"identity":"2574f8ee-d658-4351-bf3d-ef3993329828","order_by":4,"name":"Zhenglong Liang","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Zhenglong","middleName":"","lastName":"Liang","suffix":""}],"badges":[],"createdAt":"2026-02-01 04:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8753559/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8753559/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101829837,"identity":"f3312c06-abf2-4537-a6b8-4465f16d5c1d","added_by":"auto","created_at":"2026-02-04 06:11:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":778990,"visible":true,"origin":"","legend":"","description":"","filename":"Anexponentialintensitymappingmethodforgrayscaledriftsuppressioninhightemperatureforgingimages.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8753559/v1_covered_3f7a6ead-90bc-4170-93f0-c9866f420797.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An exponential intensity mapping method for grayscale drift suppression in high-temperature forging images","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"high-temperature forging; image preprocessing; Canny; region growing; machine vision","lastPublishedDoi":"10.21203/rs.3.rs-8753559/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8753559/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"High-temperature forging images often suffer from non-stationary grayscale drift caused by the formation and spallation of oxide scale. 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