Title
Texture Classification with Generalized Fourier Descriptors in Dimensionality Reduction Context: An Overview Exploration
Abstract
In the context of texture classification, this article explores the capacity and the performance of some combinations of feature extraction, linear and nonlinear dimensionality reduction techniques and several kinds of classification methods. The performances are evaluated and compared in term of classification error. In order to test our texture classification protocol, the experiment carried out images from two different sources, the well known Brodatz database and our leaf texture images database.
Year
DOI
Venue
2008
10.1007/978-3-540-69939-2_27
Lecture Notes in Computer Science
Keywords
Field
DocType
feature extraction,texture classification,classification method,texture classification protocol,brodatz database,different source,generalized fourier descriptors,overview exploration,dimensionality reduction context,leaf texture images database,classification error,nonlinear dimensionality reduction technique,nonlinear dimensionality reduction
Dimensionality reduction,Pattern recognition,Computer science,Feature extraction,Fourier transform,Artificial intelligence,Nonlinear dimensionality reduction,Machine learning
Conference
Volume
ISSN
Citations 
5064
0302-9743
3
PageRank 
References 
Authors
0.53
20
5
Name
Order
Citations
PageRank
Ludovic Journaux1155.86
Marie-France Destain242.02
Johel Miteran3807.94
Alexis Piron430.53
Frederic Cointault5164.79