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dc.creatorRuíz, O.
dc.creatorVanegas, C.
dc.creatorCadavid, C.
dc.date.available2016-11-18T22:14:34Z
dc.date.issued2011
dc.identifier.issn1432-2315spa
dc.identifier.urihttp://hdl.handle.net/10784/9681
dc.descriptionSurface reconstruction from cross cuts usually requires curve reconstruction from planar noisy point samples -- The output curves must form a possibly disconnected 1manifold for the surface reconstruction to proceed -- This article describes an implemented algorithm for the reconstruction of planar curves (1manifolds) out of noisy point samples of a sel-fintersecting or nearly sel-fintersecting planar curve C -- C:[a,b]⊂R→R is self-intersecting if C(u)=C(v), u≠v, u,v∈(a,b) (C(u) is the self-intersection point) -- We consider only transversal self-intersections, i.e. those for which the tangents of the intersecting branches at the intersection point do not coincide (C′(u)≠C′(v)) -- In the presence of noise, curves which self-intersect cannot be distinguished from curves which nearly sel fintersect -- Existing algorithms for curve reconstruction out of either noisy point samples or pixel data, do not produce a (possibly disconnected) Piecewise Linear 1manifold approaching the whole point sample -- The algorithm implemented in this work uses Principal Component Analysis (PCA) with elliptic support regions near the selfintersections -- The algorithm was successful in recovering contours out of noisy slice samples of a surface, for the Hand, Pelvis and Skull data sets -- As a test for the correctness of the obtained curves in the slice levels, they were input into an algorithm of surface reconstruction, leading to a reconstructed surface which reproduces the topological and geometrical properties of the original object -- The algorithm robustly reacts not only to statistical noncorrelation at the self-intersections(nonmanifold neighborhoods) but also to occasional high noise at the nonselfintersecting (1manifold) neighborhoodsspa
dc.formatapplication/pdfeng
dc.language.isoengspa
dc.publisherSpringer Berlin Heidelbergspa
dc.relation.ispartofThe Visual Computer, Collection: Computer Science, Volume 27, Issue 3, pp. 211-226spa
dc.relation.isversionofhttp://dx.doi.org/10.1007/s00371-010-0527-xspa
dc.rightsSpringer-Verlag 2010spa
dc.rightsinfo:eu-repo/semantics/openAccesseng
dc.subjectReconstrucción superficialspa
dc.subjectNube de puntosspa
dc.titleEllipse-based Principal Component Analysis for Self-intersecting Curve Reconstruction from Noisy Point Setsspa
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.rights.accessRightsopenAccesseng
dc.subject.lembCURVAS PLANASspa
dc.subject.lembCOLECTORES (INGENIERÍA)spa
dc.subject.lembTOPOLOGÍAspa
dc.subject.lembVARIEDADES (MATEMÁTICAS)spa
dc.subject.lembCORRELACIÓN (ESTADÍSTICA)spa
dc.subject.lembANÁLISIS ESTOCÁSTICOspa
dc.subject.lembFUNCIONES ELÍPTICASspa
dc.type.spaArtículospa
dc.subject.keywordCurves, planespa
dc.subject.keywordTopologyspa
dc.subject.keywordManifolds (Mathematics)spa
dc.subject.keywordCorrelation (statistics)spa
dc.subject.keywordStochastic analysisspa
dc.subject.keywordFunctions, ellipticspa
dc.rights.accesoLibre accesospa
dc.date.accessioned2016-11-18T22:14:34Z
dc.type.hasVersionpublishedVersionspa
dc.tipo.versionObra publicadaspa
dc.citation.journalTitleThe Visual Computerspa
dc.citation.volume27spa
dc.citation.issue3spa
dc.citation.spage211spa
dc.citation.epage226spa
dc.identifier.doi10.1007/s00371-010-0527-xspa


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