scholarly journals High Speed Holographic Optical Correlator for Face Recognition

Author(s):  
Eriko Watanabe ◽  
Kashiko Kodate
2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Kanokmon Rujirakul ◽  
Chakchai So-In ◽  
Banchar Arnonkijpanich

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages’ complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.


2014 ◽  
Vol 41 (2) ◽  
pp. 0209005
Author(s):  
易瑶 Yi Yao ◽  
曹良才 Cao Liangcai ◽  
郑天祥 Zheng Tianxiang ◽  
赵瑱 Zhao Tian ◽  
何庆声 He Qingsheng ◽  
...  

2008 ◽  
Author(s):  
D. F. Geraghty ◽  
R. Salem ◽  
M. A. Foster ◽  
A. L. Gaeta

Author(s):  
Reza Salem ◽  
Scott Nuccio ◽  
Vahid R. Arbab ◽  
Xiaoxia Wu ◽  
Mark A. Foster ◽  
...  

2015 ◽  
Vol 54 (9S) ◽  
pp. 09ME02 ◽  
Author(s):  
Kanami Ikeda ◽  
Eriko Watanabe

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