Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

This paper presents a novel approach for texture classification, generalizing the well-known
local binary pattern (LBP) approach. In the proposed approach, two different and …

Tactile texture refers to the tangible feel of a surface and visual texture refers to see the
shape or contents of the image. In the image processing, the texture can be defined as a …

Representing texture images statistically as histograms over a discrete vocabulary of local
features has proven widely effective for texture classification tasks. Images are described …

Local binary pattern (LBP) and its variants have been successfully applied in texture feature
extraction. However, it is hard for most LBP-based methods to effectively describe and …

In this survey, we present a review of methods and resources for texture recognition,
presenting the most common techniques that have been used in the recent decades, along …

In this paper, we present a novel rotation-invariant and computationally efficient texture
descriptor called Dominant Rotated Local Binary Pattern (DRLBP). A rotation invariance is …

This paper is devoted to the problem of texture classification. Motivated by recent
advancements in the field of compressive sensing and keypoints descriptors, a set of novel …

Texture classification is an important and challenging problem in many image processing
applications. While convolutional neural networks (CNNs) achieved significant successes …

Deep learning has established many new state of the art solutions in the last decade in
areas such as object, scene and speech recognition. In particular Convolutional Neural …