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dc.contributor.authorCalatroni, L
dc.contributor.authorvan Gennip, Y
dc.contributor.authorSchönlieb, CB
dc.contributor.authorRowland, Hannah
dc.contributor.authorFlenner, A
dc.date.accessioned2018-10-18T10:21:14Z
dc.date.available2018-10-18T10:21:14Z
dc.date.issued2017-02
dc.identifier.issn0924-9907
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/284119
dc.description.abstract© 2016, Springer Science+Business Media New York. We consider the problem of scale detection in images where a region of interest is present together with a measurement tool (e.g. a ruler). For the segmentation part, we focus on the graph-based method presented in Bertozzi and Flenner (Multiscale Model Simul 10(3):1090–1118, 2012) which reinterprets classical continuous Ginzburg–Landau minimisation models in a totally discrete framework. To overcome the numerical difficulties due to the large size of the images considered, we use matrix completion and splitting techniques. The scale on the measurement tool is detected via a Hough transform-based algorithm. The method is then applied to some measurement tasks arising in real-world applications such as zoology, medicine and archaeology.
dc.publisherSpringer Science and Business Media LLC
dc.titleGraph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images
dc.typeArticle
prism.endingPage291
prism.issueIdentifier2
prism.publicationDate2017
prism.publicationNameJournal of Mathematical Imaging and Vision
prism.startingPage269
prism.volume57
dc.identifier.doi10.17863/CAM.31490
dcterms.dateAccepted2017-02-01
rioxxterms.versionofrecord10.1007/s10851-016-0678-0
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2017-02-01
dc.contributor.orcidCalatroni, L [0000-0003-3887-1859]
dc.contributor.orcidRowland, Hannah [0000-0002-1040-555X]
dc.identifier.eissn1573-7683
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/J009539/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/M00483X/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/N014588/1)
pubs.funder-project-idAlan Turing Institute (unknown)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (691070)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/H023348/1)
cam.issuedOnline2016-07-25
rioxxterms.freetoread.startdate2018-02-01


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