Two decades of local binary patterns: A survey
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Dec 2016.
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Citing papers per year: 2022: 2; 2023: 3; 2024: 0; 2025: 1.
6 papers.
- 2022PCQA-GRAPHPOINT: Efficients Deep-Based Graph Metric For Point Cloud Quality Assessmentcited by 8
- 2022From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discoverycited by 4
- 2023Quality evaluation of point clouds: a novel no-reference approach using transformer-based architecturecited by 1
- 2023MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillationcited by 1
- 2023Deep Neural Networks Fused with Textures for Image Classificationcited by 1
- 2025Uncertainty-Aware Decomposed Hybrid Networkscited by 1
- 2025Uncertainty-Aware Decomposed Hybrid Networks24 Mar 2025
- 2023Deep Neural Networks Fused with Textures for Image Classification3 Aug 2023
- 2023MV-MR: multi-views and multi-representations for self-supervised learning and knowledge distillation21 Mar 2023
- 2023Quality evaluation of point clouds: a novel no-reference approach using transformer-based architecture15 Mar 2023
- 2022PCQA-GRAPHPOINT: Efficients Deep-Based Graph Metric For Point Cloud Quality Assessment4 Nov 2022
- 2022From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discovery31 May 2022