Decorrelation Methods of Texture Feature Extraction

Author

Faugeras, Olivier D. ; Pratt, William K.

Author_Institution

MEMBER, IEEE, Institut de Recherche d´´Informatique et d´´Automatique, Domaine de Voluceau, Rocquencourt, Le Chesnay, France; Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90007.

Issue

4

fYear

1980

fDate

7/1/1980 12:00:00 AM

Firstpage

323

Lastpage

332

Abstract

This paper presents the development and evaluation of a visual texture feature extraction method based on a stochastic field model of texture. Results of recent visual texture discrimination experiments are reviewed in order to establish necessary and sufficient conditions for texture features that are in agreement with human discrimination. A texture feature extraction technique involving autocorrelation function measurement of a texture field, combined with histogram representation of a statistically decorrelated version of the texture field, is introduced. The texture feature extraction method is evaluated in terms of a Bhattacharyya distance measure.

Keywords

Autocorrelation; Decorrelation; Feature extraction; Histograms; Humans; Image classification; Image texture; Pattern recognition; Pixel; Stochastic processes; Bhattacharyya distance; decorrelation; feature extraction; pattern recognition; statistical classification; texture;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/TPAMI.1980.4767031

Filename

4767031