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A Gaussian mixture-based colour texture model

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F04%3A00106294" target="_blank" >RIV/67985556:_____/04:00106294 - isvavai.cz</a>

  • Alternative codes found

    RIV/61384399:31160/04:00019178

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Gaussian mixture-based colour texture model

  • Original language description

    A new method of colour texture modelling based on Gaussian distribution mixtures is discussed. We estimate the local statistical properties of the monospectral version of the target texture in the form of a Gaussian mixture of product components. The synthesized texture is obtained by means of a step-wise prediction of the texture image. The proposed texture modelling method can be viewed as a statistically controlled sampling.

  • Czech name

    Texturní model založený na gaussovských směsích

  • Czech description

    Práce popisuje novou metodu pro modelování barevných textur založenou na pravděpodobnostním modelu typu gaussovské distribuční směsi. Odhadujeme lokální statistické vlastnosti monospektrální verze cílové textury ve formě gaussovské směsi součinových složek. Syntéza textury je založena na predikci texturního obrazu

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BD - Information theory

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2004

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 17th IAPR International Conference on Pattern Recognition

  • ISBN

    0-7695-2128-2

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    177-180

  • Publisher name

    IEEE

  • Place of publication

    Los Alamitos

  • Event location

    Cambridge

  • Event date

    Aug 23, 2004

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article