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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F09%3A00327903%21RIV10-AV0-67985556
rdf:type
skos:Concept n17:Vysledek
dcterms:description
In this paper, we present a novel multiscale texture model and a related algorithm for the unsupervised segmentation of color images. Elementary textures are characterized by their spatial interactions with neighboring regions along selected directions. Such interactions are modeled, in turn, by means of a set of Markov chains, one for each direction, whose parameters are collected in a feature vector that synthetically describes the texture. Based on the feature vectors, the texture are then recursively merged, giving rise to larger and more complex textures, which appear at different scales of observation: accordingly, the model is named Hierarchical Multiple Markov Chain (H-MMC). The Texture Fragmentation and Reconstruction (TFR) algorithm, addresses the unsupervised segmentation problem based on the H-MMC model. In this paper, we present a novel multiscale texture model and a related algorithm for the unsupervised segmentation of color images. Elementary textures are characterized by their spatial interactions with neighboring regions along selected directions. Such interactions are modeled, in turn, by means of a set of Markov chains, one for each direction, whose parameters are collected in a feature vector that synthetically describes the texture. Based on the feature vectors, the texture are then recursively merged, giving rise to larger and more complex textures, which appear at different scales of observation: accordingly, the model is named Hierarchical Multiple Markov Chain (H-MMC). The Texture Fragmentation and Reconstruction (TFR) algorithm, addresses the unsupervised segmentation problem based on the H-MMC model.
dcterms:title
Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation
skos:prefLabel
Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation
skos:notation
RIV/67985556:_____/09:00327903!RIV10-AV0-67985556
n3:aktivita
n8:P n8:Z
n3:aktivity
P(2C06019), P(GA102/08/0593), Z(AV0Z10750506)
n3:cisloPeriodika
8
n3:dodaniDat
n15:2010
n3:domaciTvurceVysledku
n6:2890542
n3:druhVysledku
n11:J
n3:duvernostUdaju
n13:S
n3:entitaPredkladatele
n12:predkladatel
n3:idSjednocenehoVysledku
317075
n3:idVysledku
RIV/67985556:_____/09:00327903
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Classification; texture analysis; segmentation; hierarchical image models; Markov process
n3:klicoveSlovo
n4:Classification n4:Markov%20process n4:texture%20analysis n4:hierarchical%20image%20models n4:segmentation
n3:kodStatuVydavatele
US - Spojené státy americké
n3:kontrolniKodProRIV
[A8639E654B89]
n3:nazevZdroje
IEEE Transactions on Image Processing
n3:obor
n9:BD
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
4
n3:projekt
n14:GA102%2F08%2F0593 n14:2C06019
n3:rokUplatneniVysledku
n15:2009
n3:svazekPeriodika
18
n3:tvurceVysledku
Zerubia, J. Haindl, Michal Gaetano, R. Scarpa, G.
n3:wos
000268033300012
n3:zamer
n18:AV0Z10750506
s:issn
1057-7149
s:numberOfPages
14