Texture analysis is used in a very broad range of fields and applications, from texture
classification (eg, for remote sensing) to segmentation (eg, in biomedical imaging), passing …

Texture classification is a very important field of image analysis. Because of this, the
literature has been presented methods that provide more and more highly discriminative …

Background Surface roughness has a significant effect on leaf wettability. Consequently, it
influences the efficiency and effectiveness of pesticide application. Therefore, roughness …

Color textures are among the most important visual attributes in image analysis. This paper
presents a novel method to analyze color textures by modeling a color image as a graph in …

Texture classification is a process of distinguishing or classifying different textures into
separate classes. Finding an efficient texture descriptor is a vital step for performing accurate …

Texture is a very important attribute in the field of computer vision. This work proposes a
novel texture analysis method which is based on graph theory. Basically, we convert the …

This paper presents an innovative manner of obtaining discriminative texture signatures by
using the LBP approach to extract additional sources of information from an input image and …

Texture analysis is gaining popularity among the scientific community. A wide variety of
applications use texture analysis method. Texture analysis methods can be used for image …

Texture and color are essential attributes to be analyzed for any robust computer vision
system. This paper presents a novel method to analyze color-texture images, based on …

In this work, we propose a novel set of fractal descriptors extracted from gray-level texture
images using Bouligand–Minkowski method. To accomplish that, we first convert the texture …