Two decades of local binary patterns: A survey

TL;DR

This survey reviews twenty years of local binary patterns (LBP), highlighting its evolution, variants, and applications across multiple domains, emphasizing its growing importance in texture analysis and image processing.

Contribution

It provides a comprehensive overview of recent LBP variants in 2D, spatiotemporal, 3D, and 4D domains, including new developments in 1D signal analysis.

Findings

LBP variants have improved robustness and discriminative power.

LBP's application scope has expanded to multiple dimensions and signals.

Future research challenges are identified.

Abstract

Texture is an important characteristic for many types of images. In recent years very discriminative and computationally efficient local texture descriptors based on local binary patterns (LBP) have been developed, which has led to significant progress in applying texture methods to different problems and applications. Due to this progress, the division between texture descriptors and more generic image or video descriptors has been disappearing. A large number of different variants of LBP have been developed to improve its robustness, and to increase its discriminative power and applicability to different types of problems. In this chapter, the most recent and important variants of LBP in 2D, spatiotemporal, 3D, and 4D domains are surveyed. Interesting new developments of LBP in 1D signal analysis are also considered. Finally, some future challenges for research are presented.