Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96613
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorQiao, Zen_US
dc.creatorZhang, Qen_US
dc.date.accessioned2022-12-08T08:06:15Z-
dc.date.available2022-12-08T08:06:15Z-
dc.identifier.issn1004-8979en_US
dc.identifier.urihttp://hdl.handle.net/10397/96613-
dc.language.isoenen_US
dc.publisherGlobal Science Pressen_US
dc.rights©2022 Global-Science Pressen_US
dc.rightsThis is the accepted version of the following article: Qiao, Z., & Zhang, Q. (2022). Two-phase image segmentation by the Allen-Cahn equation and a nonlocal edge detection operator. Numerical Mathematics: Theory, Methods and Applications, 15(4), 1147-1172, which has been published in https://doi.org/10.4208/nmtma.OA-2022-0008s.en_US
dc.subjectImage segmentationen_US
dc.subjectAllen-Cahn equationen_US
dc.subjectNonlocal edge detection operatoren_US
dc.subjectMaximum principleen_US
dc.subjectEnergy stabilityen_US
dc.titleTwo-phase image segmentation by the Allen-Cahn equation and a nonlocal edge detection operatoren_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1147en_US
dc.identifier.epage1172en_US
dc.identifier.volume15en_US
dc.identifier.issue4en_US
dc.identifier.doi10.4208/nmtma.OA-2022-0008sen_US
dcterms.abstractBased on a nonlocal Laplacian operator, a novel edge detection method of the grayscale image is proposed in this paper. This operator utilizes the information of neighbor pixels for a given pixel to obtain effective and delicate edge detection. The nonlocal edge detection method is used as an initialization for solving the Allen-Cahn equation to achieve two-phase segmentation of the grayscale image. Efficient exponential time differencing (ETD) solvers are employed in the time integration, and finite difference method is adopted in space discretization. The maximum bound principle and energy stability of the proposed numerical schemes are proved. The capability of our segmentation method has been verified in numerical experiments for different types of grayscale images.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationNumerical mathematics : theory, methods and applications, 2022, v. 15, no. 4, p. 1147-1172en_US
dcterms.isPartOfNumerical mathematics : theory, methods and applicationsen_US
dcterms.issued2022-
dc.identifier.eissn2079-7338en_US
dc.description.validate202212 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1849-
dc.identifier.SubFormID46027-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Scholar Programen_US
dc.description.pubStatusPublisheden_US
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