About: Unsupervised Hierarchical Weighted Multi-Segmenter

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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)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	An unsupervised multi-spectral, multi-resolution, multiple-segmenter for textured images with unknown number of classes is presented. The segmenter is based on a weighted combination of several unsupervised segmentation results, each in different resolution, using the modified sum rule. Multi-spectral textured image mosaics are locally represented by four causal directional multi-spectral random field models recursively evaluated for each pixel. The single-resolution segmentation part of the algorithm is based on the underlying Gaussian mixture model and starts with an over segmented initial estimation which is adaptively modified until the optimal number of homogeneous texture segments is reached. The performance of the presented method is extensively tested on the Prague segmentation benchmark using the commonest segmentation criteria and compares favourably with several leading alternative image segmentation methods. An unsupervised multi-spectral, multi-resolution, multiple-segmenter for textured images with unknown number of classes is presented. The segmenter is based on a weighted combination of several unsupervised segmentation results, each in different resolution, using the modified sum rule. Multi-spectral textured image mosaics are locally represented by four causal directional multi-spectral random field models recursively evaluated for each pixel. The single-resolution segmentation part of the algorithm is based on the underlying Gaussian mixture model and starts with an over segmented initial estimation which is adaptively modified until the optimal number of homogeneous texture segments is reached. The performance of the presented method is extensively tested on the Prague segmentation benchmark using the commonest segmentation criteria and compares favourably with several leading alternative image segmentation methods. (en)
Title	Unsupervised Hierarchical Weighted Multi-Segmenter Unsupervised Hierarchical Weighted Multi-Segmenter (en)
skos:prefLabel	Unsupervised Hierarchical Weighted Multi-Segmenter Unsupervised Hierarchical Weighted Multi-Segmenter (en)
skos:notation	RIV/67985556:_____/09:00327029!RIV10-MSM-67985556
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(1M0572), P(2C06019), P(GA102/08/0593), Z(AV0Z10750506)
http://linked.open...vai/riv/dodaniDat	2010
http://linked.open...aciTvurceVysledku	Haindl, Michal Pudil, Pavel Mikeš, Stanislav
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	347674
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/09:00327029
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	unsupervised image segmentation (en)
http://linked.open.../riv/klicoveSlovo	unsupervised image segmentation
http://linked.open...ontrolniKodProRIV	[6124C8388BDA]
http://linked.open...v/mistoKonaniAkce	Reykjavik
http://linked.open...i/riv/mistoVydani	Berlin Heidelberg
http://linked.open...i/riv/nazevZdroje	Multiple Classifier Systems, LNCS 5519
http://linked.open...in/vavai/riv/obor	BD
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Data, algorithms, decision making (Medical) Knowledge Acquisition and Modelling BTF Texture Modelling
http://linked.open...UplatneniVysledku	2009
http://linked.open...iv/tvurceVysledku	Haindl, Michal Pudil, Pavel Mikeš, Stanislav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2009-06-10 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Pokročilé matematické metody získávání, zpracování a využití informací a znalostí ve složitých a nedeterministických systémech
number of pages	11 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	3-642-02325-8

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