Extraction of noise robust rotation invariant texture features via multichannel filtering

Author

Fountain, S.R. ; Tan, T.N.

Author_Institution

Reading Univ., UK

Volume

3

fYear

1997

fDate

26-29 Oct 1997

Firstpage

197

Abstract

An efficient and accurate method of extracting rotation invariant texture features via a multichannel Gabor filtering technique is presented. A main focus of the paper is a thorough investigation into the optimum parameter settings for the method. Experiments include the exploration of different frequency combinations, sampling intervals and number of features. The optimum settings are used to test the method´s texture classification abilities on a database of over 1320 images originating from 44 different texture classes. The resistance to noise is measured via the addition of various levels of Gaussian noise to each image before classification

Keywords

Gaussian noise; feature extraction; filtering theory; image classification; image sampling; image texture; Gabor filtering; Gaussian noise; feature extraction; frequency combinations; image texture classification; multichannel filtering; noise resistance; noise robust rotation invariant texture features; number of features; optimum parameter settings; sampling intervals; Filtering; Focusing; Frequency; Gabor filters; Gaussian noise; Image databases; Image sampling; Noise robustness; Spatial databases; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.632053

Filename

632053