About: Smooth Chan-Vese Segmentation via Graph Cuts

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.sciencedirect.com/science/article/pii/S0167865512000955
Description	The graph cut framework presents an efficient method for approximating the minimum of the popular Chan-Vese functional for image segmentation. However, a fundamental drawback of graph cuts is a need for a dense neighbourhood system in order to avoid geometric artefacts and jagged boundaries. The increasing connectivity leads to excessive memory consumption and burdens the efficiency of the method. In this paper, we address the issue by introducing a two-stage connectivity scaling approach. First, coarse segmentation is calculated using a sparse neighbourhood over the whole image. In the second stage, the segmentation is refined by employing a dense neighbourhood in a narrow band around the boundary from the first stage. We demonstrate that this method fits well with the Chan-Vese functional and yields smooth boundaries without increasing the computational demands significantly. Moreover, under specific conditions, the construction has no negative effect on the optimality of the solution. The graph cut framework presents an efficient method for approximating the minimum of the popular Chan-Vese functional for image segmentation. However, a fundamental drawback of graph cuts is a need for a dense neighbourhood system in order to avoid geometric artefacts and jagged boundaries. The increasing connectivity leads to excessive memory consumption and burdens the efficiency of the method. In this paper, we address the issue by introducing a two-stage connectivity scaling approach. First, coarse segmentation is calculated using a sparse neighbourhood over the whole image. In the second stage, the segmentation is refined by employing a dense neighbourhood in a narrow band around the boundary from the first stage. We demonstrate that this method fits well with the Chan-Vese functional and yields smooth boundaries without increasing the computational demands significantly. Moreover, under specific conditions, the construction has no negative effect on the optimality of the solution. (en)
Title	Smooth Chan-Vese Segmentation via Graph Cuts Smooth Chan-Vese Segmentation via Graph Cuts (en)
skos:prefLabel	Smooth Chan-Vese Segmentation via Graph Cuts Smooth Chan-Vese Segmentation via Graph Cuts (en)
skos:notation	RIV/00216224:14330/12:00057198!RIV13-GA0-14330___
http://linked.open...avai/riv/aktivita	P S Z
http://linked.open...avai/riv/aktivity	P(2B06052), P(GBP302/12/G157), P(LC535), S, Z(MSM0021622419)
http://linked.open...iv/cisloPeriodika	10
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Kozubek, Michal Daněk, Ondřej Matula, Pavel
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Fakulta informatiky
http://linked.open...dnocenehoVysledku	168640
http://linked.open...ai/riv/idVysledku	RIV/00216224:14330/12:00057198
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	image segmentation; graph cut framework; Chan-Vese model; boundary smoothness; memory consumption (en)
http://linked.open.../riv/klicoveSlovo	Chan-Vese model boundary smoothness graph cut framework memory consumption image segmentation
http://linked.open...odStatuVydavatele	NL - Nizozemsko
http://linked.open...ontrolniKodProRIV	[880E605881AE]
http://linked.open...i/riv/nazevZdroje	Pattern Recognition Letters
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Determination of markers, screening and early diagnostics of cancer diseases using highly automated processing of multidimensional biomedical images Chromosome dynamics and organization during the cell cycle in normal and pathologic conditions Dynamics and Organization of Chromosomes in the Cell Cycle and during Differentiation under Normal and Pathological Conditions
http://linked.open...UplatneniVysledku	2012
http://linked.open...v/svazekPeriodika	33
http://linked.open...iv/tvurceVysledku	Daněk, Ondřej Matula, Pavel Maška, Martin Kozubek, Michal
http://linked.open...ain/vavai/riv/wos	000305771400018
http://linked.open...n/vavai/riv/zamer	Highly Parallel and Distributed Computing Systems
issn	0167-8655
number of pages	6 (xsd:int)
http://bibframe.org/vocab/doi	10.1016/j.patrec.2012.03.013
http://localhost/t...ganizacniJednotka	14330

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