Color Texture Segmentation by Decomposition of Gaussian Mixture Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F06%3A00041781" target="_blank" >RIV/67985556:_____/06:00041781 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Color Texture Segmentation by Decomposition of Gaussian Mixture Model
Original language description
Recently we have proposed Gaussian mixtures as a local statistical model to synthesize artificial textures. We describe the statistical dependence of pixels of a movable window by multivariate Gaussian mixture of product components. The mixture components correspond to different variants of image patches as they appear in the window. In this sense they can be used to identify different segments of the source color texture image. The segmentation can be obtained by means of Bayes formula provided that aproper decomposition of the estimated Gaussian mixture into sub-mixtures is available. In this paper the mixture model is decomposed by maximizing the mean probability of correct classification of pixels into segments in a way taking into account the assumed consistency of final segmentation.
Czech name
Segmentace barevné textury dekompozicí modelu textury ve tvaru normální směsi
Czech description
Metoda je založena na lokálním statistickém modelu textury ve tvaru normální distribuční směsi, která popisuje statistické závislosti pixelů v rozsahu zvoleného pohyblivého okna. V práci je navržen algoritmus umožňující dekompozici směsi na části popisující jednotlivé segmenty textury.
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Computer Science
ISSN
0302-9743
e-ISSN
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Volume of the periodical
19
Issue of the periodical within the volume
4225
Country of publishing house
DE - GERMANY
Number of pages
10
Pages from-to
287-296
UT code for WoS article
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EID of the result in the Scopus database
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