A Gaussian mixture-based colour texture model

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 ste...

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Bibliographic Details
Published inProceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004 Vol. 3; pp. 177 - 180 Vol.3
Main Authors Haindl, M., Grim, J., Somol, P., Pudil, P., Kudo, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2004
Subjects
Artificial intelligence
Automation
Chromium
Control system synthesis
Gaussian distribution
Image sampling
Information theory
Mathematical model
Parameter estimation
Sampling methods
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Summary: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. In order to achieve a realistic colour texture image and to avoid possible loss of high-frequency details we use optimally chosen pieces of the original colour source texture in the synthesis phase. In this sense the proposed texture modelling method can be viewed as a statistically controlled sampling. By using multispectral or mutually registered BTF texture pieces the method can be easily extended also for these textures.
ISBN:0769521282
9780769521282
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2004.1334497