Home >>Journals >>ICTACT Journal on Image and Video Processing ( Volume: 4 , Issue: 4 )
FUSION OF WAVELET AND CURVELET COEFFICIENTS FOR GRAY TEXTURE CLASSIFICATION
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff9a4716000000d059010001000200
This study presents a framework for gray texture classification based on the fusion of wavelet and curvelet features. The two main frequency domain transformations Discrete Wavelet Transform (DWT) and Discrete Curvelet Transform (DCT) are analyzed. The features are extracted from the DWT and DCT decomposed image separately and their performance is evaluated independently. Then feature fusion technique is applied to increase the classification accuracy of the proposed approach. Brodatz texture images are used for this study. The results show that, only two texture images D105 and D106 are misclassified by the fusion approach and 99.74% classification accuracy is obtained.

Authors
M. Santhanalakshmi1, K. Nirmala2
Manonmaniam Sundaranar University, India1, Quaid-e-Millath Government College for Women, India2

Keywords
Texture Classification, Wavelet Transform, Curvelet Transform, Nearest Neighbor Classifier, Brodatz Album
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
000000000000
Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 4 , Issue: 4 , Pages: 805-811 )
Date of Publication :
May 2014
Page Views :
113
Full Text Views :

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.