Designing discriminative powerful texture features robust to realistic imaging conditions is a
challenging computer vision problem with many applications, including material recognition …

Texture, along with color, is one of the most important characteristics of a material defining
its appearance. While color had been studied for a long time and continues being an …

A new texture representation framework called statistical binary patterns (SBPs) is
presented. It consists in applying rotation invariant local binary pattern operators (LBP riu 2) …

Fine-grained visual classification (FGVC) is a challenging computer vision problem, where
the task is to automatically recognise objects from subordinate categories. One of its main …

Texture classification plays a major role in many computer vision applications. Local binary
patterns (LBP) encoding schemes have largely been proven to be very effective for this task …

In this article we provide an overview of color name applications in computer vision. Color
names are linguistic labels which humans use to communicate color. Computational color …

Purpose The purpose of this paper is to propose a color-texture classification approach
which uses color sensor information and texture features jointly. High accuracy, low noise …

With the development of Information technology and communication, a large part of the
databases is dedicated to images and videos. Thus retrieving images related to a query …

Aerial scene classification is a challenging problem in understanding high-resolution remote
sensing images. Most recent aerial scene classification approaches are based on …

Texture classification is an active topic in image processing which plays an important role in
many applications such as image retrieval, inspection systems, face recognition, medical …