Two decades of local binary patterns: A survey

December 20, 2016 Β· The Cartographer Β· πŸ› arXiv.org

πŸ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper β€” maps the landscape rather than implementing a method.

"No code URL or promise found in abstract"
"Title-pattern auto-detect: Two decades of local binary patterns: A survey"

Evidence collected by the PWNC Scanner

Authors Matti PietikΓ€inen, Guoying Zhao arXiv ID 1612.06795 Category cs.CV: Computer Vision Citations 77 Venue arXiv.org Last Checked 1 day ago
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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Computer Vision

πŸŒ… πŸŒ… Old Age

Fast R-CNN

Ross Girshick

cs.CV πŸ› ICCV πŸ“š 27.7K cites 11 years ago