Multiscale skeletons by image foresting transform and its application to neuromorphometry

dc.creatorFalcao, AX
dc.creatorCosta, LD
dc.creatorda Cunha, BS
dc.date2002
dc.dateJUL
dc.date2014-11-14T23:16:38Z
dc.date2015-11-26T17:17:45Z
dc.date2014-11-14T23:16:38Z
dc.date2015-11-26T17:17:45Z
dc.date.accessioned2018-03-29T00:05:36Z
dc.date.available2018-03-29T00:05:36Z
dc.identifierPattern Recognition. Pergamon-elsevier Science Ltd, v. 35, n. 7, n. 1571, n. 1582, 2002.
dc.identifier0031-3203
dc.identifierWOS:000175237700011
dc.identifier10.1016/S0031-3203(01)00148-0
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/82038
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/82038
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/82038
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1282523
dc.descriptionThe image foresting transform (IFT) reduces optimal image partition problems based on seed pixels to a shortest-path forest problem in a graph, whose solution can be obtained in linear time. Such a strategy has allowed a unified and efficient approach to the design of image processing operators, such as edge tracking, region growing, watershed transforms, distance transforms, and connected filters. This paper presents a fast and simple method based on the IFT to compute multiscale skeletons and shape reconstructions without border shifting. The method also generates one-pixel-wide connected skeletons and the skeleton by influence zones, simultaneously, for objects of arbitrary topologies. The results of the work are illustrated with respect to skeleton quality, execution time, and its application to neuromorphometry. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
dc.description35
dc.description7
dc.description1571
dc.description1582
dc.languageen
dc.publisherPergamon-elsevier Science Ltd
dc.publisherOxford
dc.publisherInglaterra
dc.relationPattern Recognition
dc.relationPattern Recognit.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectmultiscale skeletons
dc.subjectshape filtering
dc.subjectimage analysis
dc.subjectlinage foresting transform
dc.subjectEuclidean distance transform
dc.subjectexact dilations
dc.subjectlabel propagation
dc.subjectneuromorphometry
dc.subjectgraph algorithms
dc.subjectMorphometric Characterization
dc.subjectShape Representation
dc.subjectGanglion-cells
dc.subjectRabbit Retina
dc.subjectNeural Cells
dc.subjectMorphology
dc.titleMultiscale skeletons by image foresting transform and its application to neuromorphometry
dc.typeArtículos de revistas


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