peer reviewedIn 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. © 2008 Springer-Verlag Berlin Heidelberg
High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultura...
The present work proposes the development of a novel method to provide descriptors for colored textu...
Textures play important roles in many image processing applications, since images of real objects of...
Dans un contexte de classification de texture par caractérisation d'invariant, cet article propose d...
Texture plays an increasingly important role in computer vision. It has found wide application in re...
International audienceIn the context of leaf roughness study for precision spray- ing applications, ...
International audienceThis paper presents an improved version of the features based on Discrete Four...
A texture descriptor is a collection of quantified measurements of a texture’s properties. They are ...
6 pages in IEEE formatThis paper presents an empirical comparison of two texture descriptors reporte...
This paper proposes a new texture classification approach. There are two main contributions in the p...
Texture-based recognition for image segmentation and classification is very important in many domai...
AbstractRecently, researchers have started using texture for data visualization. The rationale behin...
Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a criti...
This thesis investigates the signal processing methods for texture classification. Most of these met...
In this thesis we present contributions related to texture detection and discrimination to be used ...
High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultura...
The present work proposes the development of a novel method to provide descriptors for colored textu...
Textures play important roles in many image processing applications, since images of real objects of...
Dans un contexte de classification de texture par caractérisation d'invariant, cet article propose d...
Texture plays an increasingly important role in computer vision. It has found wide application in re...
International audienceIn the context of leaf roughness study for precision spray- ing applications, ...
International audienceThis paper presents an improved version of the features based on Discrete Four...
A texture descriptor is a collection of quantified measurements of a texture’s properties. They are ...
6 pages in IEEE formatThis paper presents an empirical comparison of two texture descriptors reporte...
This paper proposes a new texture classification approach. There are two main contributions in the p...
Texture-based recognition for image segmentation and classification is very important in many domai...
AbstractRecently, researchers have started using texture for data visualization. The rationale behin...
Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a criti...
This thesis investigates the signal processing methods for texture classification. Most of these met...
In this thesis we present contributions related to texture detection and discrimination to be used ...
High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultura...
The present work proposes the development of a novel method to provide descriptors for colored textu...
Textures play important roles in many image processing applications, since images of real objects of...