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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F13%3A86088520%21RIV14-MSM-27240___
rdf:type
skos:Concept n12:Vysledek
dcterms:description
Segmentation is one of the most discussed problems in image processing. Many various methods for image segmentation exist. The mean-shift method is one of them and it was widely developed in recent years and it is still being developed. In this paper, we propose a new method called Layered Mean Shift that uses multiple mean-shift segmentations with different bandwidths stacked for elimination of the over-segmentation problem and finding the most appropriate segment boundaries. This method effectively reduces the need for the use of large kernels in the mean-shift method. Therefore, it also significantly reduces the computational complexity Segmentation is one of the most discussed problems in image processing. Many various methods for image segmentation exist. The mean-shift method is one of them and it was widely developed in recent years and it is still being developed. In this paper, we propose a new method called Layered Mean Shift that uses multiple mean-shift segmentations with different bandwidths stacked for elimination of the over-segmentation problem and finding the most appropriate segment boundaries. This method effectively reduces the need for the use of large kernels in the mean-shift method. Therefore, it also significantly reduces the computational complexity
dcterms:title
Layered mean shift methods Layered mean shift methods
skos:prefLabel
Layered mean shift methods Layered mean shift methods
skos:notation
RIV/61989100:27240/13:86088520!RIV14-MSM-27240___
n12:predkladatel
n13:orjk%3A27240
n4:aktivita
n20:S
n4:aktivity
S
n4:dodaniDat
n9:2014
n4:domaciTvurceVysledku
n5:5185297 n5:9112995 n5:4899423 n5:3014622
n4:druhVysledku
n14:D
n4:duvernostUdaju
n7:S
n4:entitaPredkladatele
n21:predkladatel
n4:idSjednocenehoVysledku
84441
n4:idVysledku
RIV/61989100:27240/13:86088520
n4:jazykVysledku
n16:eng
n4:klicovaSlova
segmentation; over-segmentation; mean shift; layer; image
n4:klicoveSlovo
n8:image n8:over-segmentation n8:segmentation n8:mean%20shift n8:layer
n4:kontrolniKodProRIV
[85D13A75A9DF]
n4:mistoKonaniAkce
Leibnitz
n4:mistoVydani
Berlin
n4:nazevZdroje
Lecture Notes in Computer Science. Volume 7893
n4:obor
n17:IN
n4:pocetDomacichTvurcuVysledku
4
n4:pocetTvurcuVysledku
4
n4:rokUplatneniVysledku
n9:2013
n4:tvurceVysledku
Sojka, Eduard Mozdřeň, Karel Fusek, Radovan Šurkala, Milan
n4:typAkce
n22:WRD
n4:zahajeniAkce
2013-06-02+02:00
s:issn
0302-9743
s:numberOfPages
12
n18:doi
10.1007/978-3-642-38267-3_39
n15:hasPublisher
Springer-Verlag
n6:isbn
978-3-642-38266-6
n19:organizacniJednotka
27240