DocumentCode :
2581600
Title :
(2D)2PCA-ICA: A new approach for face representation and recognition
Author :
Jeong, Dongmin ; Lee, Minho ; Ban, Sang-Woo
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Kyungpook Nat. Univ., Taegu, South Korea
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
1792
Lastpage :
1797
Abstract :
In this paper, a new feature extraction algorithm considering both two-directional two-dimensional principal component analysis ((2D)2PCA) and independent component analysis (ICA), called (2D)2PCA-ICA, is proposed for face representation. This algorithm analyzes the principal components of image vectors on 2D matrices by simultaneously considering the row and column directions as opposed to the standard PCA based on 1D vectors, and transforming those principal components to the independent components that maximize the non-Gaussianity of the sources. These two major techniques such as (2D)2PCA and ICA are used sequentially in order to obtain the most efficient features that properly describe a whole set of human faces in face databases. The proposed algorithm is applied to the face recognition problem. Simulation results on ORL and Yale B face databases shows that the proposed algorithm achieves high average success rate in face recognition compared with other models.
Keywords :
face recognition; feature extraction; image representation; independent component analysis; principal component analysis; (2D)2PCA-ICA; ORL face databases; Yale B face databases; face recognition; face representation approach; feature extraction algorithm; independent component analysis; two-directional two-dimensional principal component analysis; Algorithm design and analysis; Covariance matrix; Face recognition; Feature extraction; Humans; Image databases; Independent component analysis; Principal component analysis; Signal processing algorithms; Spatial databases; (2D)2PCA; 2DPCA; ICA; face recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5346886
Filename :
5346886
Link To Document :
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