Motivated by researching new image texture modeling that improves state-of-the-art LBP
variants and non-LBP descriptors, this paper proposes a novel approach for constructing …

In this paper, the three level descriptions from LTP and the directional features from LDP are
combined to form a new local feature descriptor, referred to as local directional ternary …

This paper presents new modeling of local binary patterns for texture representation.
Referred to as local binary gradient contours (LBGC), the proposed models are expected to …

Building discriminative and robust texture representation to deal with the changes of texture
appearance is a fundamental issue in texture classification. The Local Binary Pattern (LBP) …

Aiming at the defect of Local Binary Pattern (LBP) and its variants, this paper presents a new
modeling of the conventional LBP operator for texture classification. Named Attractive-and …

Visual texture classification plays a critical role in computer vision and pattern recognition.
As one of the most popular texture descriptors, local binary pattern (LBP) has achieved …

Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …

This paper presents a simple, efficient, yet robust approach, named joint-scale local binary
pattern (JLBP), for texture classification. In the proposed approach, the joint-scale strategy is …

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 …

Local binary patterns (LBP) are considered among the most computationally efficient high-
performance texture features. However, the LBP method is very sensitive to image noise and …