Paper Info
Title
Texture analysis and classification using bottom-up tree-structured wavelet transform
Abstract
One difficulty in texture analysis was the lack of adequate tools for characterizing textures. Recent developments in multiresolution analysis, such as the wavelet transform, attempt to overcome this difficulty. The tree-structured wavelet transform (TSWT), which affords for an analysis in terms of the texture’s decomposition structure and the corresponding spectrum in the space-frequency domain, has received a lot of attention. Recently, Chang [1] proposed a texture classification algorithm based on a top-down TSWT (TSWTTD). Although high classification rates were reported, its performance is highly dependent on a set of parameters which have to be determined through elaborate tuning. We propose a texture classification algorithm based on a bottom-up TSWT (TSWTBU), which is not dependent on ad-hoc parameters and shows also superior performance. We also provide an analysis of the structural stability of TSWT.
Year
DOI
Venue
2000
10.1007/3-540-44533-1_91
PRICAI
Keywords
Field
DocType
texture analysis,bottom up,tree structure,multiresolution analysis,top down,wavelet transform,spectrum,structural stability
Texture compression,Pattern recognition,Computer science,Second-generation wavelet transform,Artificial intelligence,Discrete wavelet transform,Stationary wavelet transform,Wavelet packet decomposition,Texture filtering,Wavelet,Wavelet transform
Conference
ISBN
Citations 
PageRank 
3-540-67925-1
0
0.34
References 
Authors
1
3
Name
Order
Citations
PageRank
Yukinobu Miyamoto101.01
Mahdad Nouri Shirazi2123.52
Kuniaki Uehara349184.76