Texture classification by means of HMM modeling of AM-FM features

Author

Salles, E.O.T. ; Lee, L.L.

Author_Institution

Departamento de Engenharia Eletrica, Univ. Fed. do Espirito Santo, Vitoria, Brazil

Volume

3

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

182

Abstract

This paper studies the classification problem of non-rotated and rotated textures digitized from the Phil Brodatz Album. The proposed texture analysis technique is based on AM-FM characterization followed by HMM modeling. The detection of AM-FM features was performed via a Gabor filter bank presented in a multiresolution way. To solve the problem of texture rotation, a technique was applied to correct the inherent orientation. In both cases, rotated and non-rotated textures, a low order feature vector was obtained from instantaneous AM-FM 2D maps. The proposed method was tested extensively and compared with some well-known approaches in the literature

Keywords

channel bank filters; feature extraction; hidden Markov models; image texture; pattern classification; AM-FM features; Gabor filter bank; HMM modeling; Phil Brodatz Album; amplitude features; frequency features; low order feature vector; nonrotated textures; rotated textures; texture classification; Computer vision; Digital images; Frequency; Gabor filters; Hidden Markov models; Image analysis; Image texture analysis; Industry applications; Pattern analysis; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2001. Proceedings. 2001 International Conference on

Conference_Location

Thessaloniki

Print_ISBN

0-7803-6725-1

Type

conf

DOI

10.1109/ICIP.2001.958081

Filename

958081