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.

Index Terms—Compressive sensing, binary robust independent elementary feature (BRIEF), descriptor.

Jinhong Zhang and Xiangwei Liu are with Bo Hai Shipbuilding Vocational College, Huludao, Liaoning, China (email: lxqlxq21@gmail.com).
Xueqing Liu is with School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China.

Cite: Jinhong Zhang, Xueqing Liu, 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.