Face Recognition using PCA versus ICA versus LDA cascaded with the neural classifier of Concurrent Self-Organizing Maps

Author

Neagoe, Victor-Emil ; Mugioiu, Alexandru-Cristian ; Stanculescu, Ioan-Anton

Author_Institution

Dept. Electron., Telecomm. & Inform. Technol., Politeh. Univ. of Bucharest, Bucharest, Romania

fYear

2010

fDate

10-12 June 2010

Firstpage

225

Lastpage

228

Abstract

We present a comparison of three feature selection methods for face recognition: Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA). One also considers evaluation of the neural classifier based on Concurrent Self-Organizing Maps, (CSOM), previously introduced by first author of this paper. The ORL Database of Faces is used for experiments and the corresponding results of evaluation are given.

Keywords

face recognition; feature extraction; independent component analysis; neural nets; principal component analysis; ICA; LDA; PCA; concurrent self-organizing maps; face recognition; feature selection methods; independent component analysis; linear discriminant analysis; neural classifier; principal component analysis; Biometrics; Face recognition; Independent component analysis; Linear discriminant analysis; Pattern recognition; Principal component analysis; Self organizing feature maps; Surveillance; Telecommunications; Terrorism; CSOM; ICA; LDA; PCA; SOM; face recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications (COMM), 2010 8th International Conference on

Conference_Location

Bucharest

Print_ISBN

978-1-4244-6360-2

Type

conf

DOI

10.1109/ICCOMM.2010.5509041

Filename

5509041