Fuzzy texture unsupervised classification approach using conditional local variance model

Author

Velloso, M.L.F. ; Souza, F.J. ; Almeida, N.N.

Author_Institution

Dept. of Electron. Eng., Rio de Janeiro State Univ., Brazil

Volume

1

fYear

2004

fDate

27-30 June 2004

Firstpage

491

Abstract

This paper presents a fuzzy-based unsupervised segmentation of textured images. We treated texture features and color features separately. Fuzzy-based homogeneity decision is used to measure the similarity of regions by making a soft fusion of texture features and color features. Texture model, the Multiplicative Autoregressive Random Field with Conditional variance (MARC), uses a neighborhood-dependent conditional variance.

Keywords

autoregressive processes; feature extraction; fuzzy logic; image classification; image colour analysis; image segmentation; image texture; random processes; unsupervised learning; conditional local variance model; fuzzy based homogeneity decision; fuzzy based unsupervised segmentation; fuzzy texture model; image colour analysis; image segmentation; multiplicative autoregressive random field; neighborhood dependent conditional variance; textured images; unsupervised image classification; Feature extraction; Image analysis; Image classification; Image processing; Image resolution; Image segmentation; Image texture analysis; Information analysis; Remote sensing; Spatial resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information, 2004. Processing NAFIPS '04. IEEE Annual Meeting of the

Print_ISBN

0-7803-8376-1

Type

conf

DOI

10.1109/NAFIPS.2004.1336332

Filename

1336332