doi: 10.17706/ijapm.2015.5.1.67-75
Design of Binary Robust Independent Elementary Features through Compressive Sensing View
,
,
Xiangwei Liu
1
- 1 Bo Hai Shipbuilding Vocational College, Huludao, Liaoning, China
- 2 School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China.
Abstract
Binary Robust Independent Elementary Feature (BRIEF) is designed to be a very simple and efficient feature point descriptor for image. In this paper, compressive sensing theory is used in proposing the reason why it works and guiding the parameter determination of BRIEF. It is proved in this paper BRIEF is the Binarization of Compressive Sensing Sampling. Also, with theoretical basis for BRIEF, there is guidance for us to design new descriptors.
Keywords
- Compressive sensing
- binary robust independent elementary feature (BRIEF)
- descriptor
How to Cite
Jinhong Zhang, Xueqing Liu, and Xiangwei Liu, "Design of Binary Robust Independent Elementary Features through Compressive Sensing View," International Journal of Applied Physics and Mathematics, vol. 5, no. 1, pp. 67-75, 2015. https://doi.org/ 10.17706/ijapm.2015.5.1.67-75
Copyright & License
Copyright © 2015 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).