Title :
Identity recognition of plantar pressure image based on compressed sensing
Author :
Yan Zhang ; Ming Zhu ; Dong Liang ; Yining Sun
Author_Institution :
Key Lab. of Intell. Comput. & Signal, Process. of Minist. of Educ., Anhui Univ., Hefei, China
Abstract :
Herein, a new identity recognition method of plantar pressure image (PPI) was investigated based on compressed sensing. During the process of identity recognition, the PPIs were collected with platform system in normal walking speed. The sparse representation of PPI was then obtained according to the sparse basis (i.e., wavelet basis). Finally, measurement vectors were calculated by the Topelitz measurement matrix and the PPI was recognized by compressed sensing classifier. The results showed that the accuracy of identity recognition of PPI based on compressed sensing exceeded 97.76%, demonstrating the effectiveness and stability of the Topelitz-compressed sensing algorithm. Meanwhile, the method used in this study reduced the data storage amount and increased the real-time recognition during the PPI process.
Keywords :
biometrics (access control); compressed sensing; image classification; image representation; matrix algebra; wavelet transforms; PPI sparse representation; Topelitz measurement matrix; Topelitz-compressed sensing algorithm; compressed sensing classifier; measurement vectors; normal walking speed; plantar pressure image identity recognition; platform system; sparse basis; wavelet basis; Accuracy; Classification algorithms; Compressed sensing; Foot; Image recognition; Sparse matrices; Support vector machine classification; Biometrics; Topelitz matrix; compressed sensing; plantar pressure image;
Conference_Titel :
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
Conference_Location :
Shengyang
Print_ISBN :
978-1-4799-2564-3
DOI :
10.1109/MEC.2013.6885562
