ORACM: Online region-based active contour model

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dc.authoridTalu, Muhammed Fatih/0000-0003-1166-8404
dc.authorwosidTalu, Muhammed Fatih/W-2834-2017
dc.contributor.authorTalu, M. Fatih
dc.date.accessioned2024-08-04T20:37:42Z
dc.date.available2024-08-04T20:37:42Z
dc.date.issued2013
dc.departmentİnönü Üniversitesien_US
dc.description.abstractA new online region-based active contour model (ORACM) is proposed in this paper. The classical geodesic active contour (GAC) model has only local segmentation property, although the Chan-Vese (C-V) model possesses global. An up-to-date active contour model (ACM with SBGFRLS) proposed in Zhang, Zhang, Song, and Zhou (2010) both has the properties of global/local segmentation and incorporates the GAC and the C-V models to raise active contours' performance on image segmentation. However it has two major disadvantages. First, it deforms the active contour model just using the gradient of current level set iteratively and so works too slowly. Second, it needs a parameter a which plays major impact on the results and to be tuned according to input images. The proposed model ORACM eliminates these two disadvantages by using a new binary level set formula and a new regularization operation such as morphological opening and closing. Without changing segmentation accuracy, ORACM requires no parameter and less time over the traditional ACMs. Experiments on synthetic and real images demonstrate that the computational cost of ORACM with the morphological operations is 3.75 times less than the traditional ACMs on average. (C) 2013 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipInonu University Scientific Research Projects Uniten_US
dc.description.sponsorshipThis research was funded by the Inonu University Scientific Research Projects Unit in number of the project 2012/13. The obtained minimum time and iteration values for each image in Table 1 are represented as bold.en_US
dc.identifier.doi10.1016/j.eswa.2013.05.056
dc.identifier.endpage6240en_US
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.issue16en_US
dc.identifier.scopus2-s2.0-84879486715en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage6233en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2013.05.056
dc.identifier.urihttps://hdl.handle.net/11616/96114
dc.identifier.volume40en_US
dc.identifier.wosWOS:000322857200002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectActive contour modelsen_US
dc.subjectOnline segmentationen_US
dc.subjectLevel set methoden_US
dc.subjectRegion-based snakesen_US
dc.subjectImage segmentationen_US
dc.titleORACM: Online region-based active contour modelen_US
dc.typeArticleen_US

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