DocumentCode :
2705450
Title :
Face Recognition Using PCA and DCT
Author :
Akrouf, Samir ; Sehili, Med Amine ; Chakhchoukh, Abdesslem ; Mostefai, Messaoud ; Youssef, Chahir
fYear :
2009
fDate :
28-30 Dec. 2009
Firstpage :
15
Lastpage :
19
Abstract :
Research in the field of face recognition knew considerable progress during these last years. Among the most evoked techniques we find those which employ the optimization of the size of the data in order to get a representation which makes it possible to carry out the recognition. For these methods, the images of faces are seen like points in a space of very great dimensions. The basic idea is to encode the initial data to pass to another space of dimensions much more reduced while preserving as much useful information. This paper presents a hybrid method combining principal components analysis (PCA) and the discrete cosine transform (DCT).
Keywords :
Computer science; Covariance matrix; Data mining; Discrete cosine transforms; Eigenvalues and eigenfunctions; Face recognition; Laboratories; Micromechanical devices; Pattern recognition; Principal component analysis; DCT; Face Recognition; PCA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
MEMS, NANO, and Smart Systems (ICMENS), 2009 Fifth International Conference on
Conference_Location :
Dubai, United Arab Emirates
Print_ISBN :
978-0-7695-3938-6
Electronic_ISBN :
978-1-4244-5616-1
Type :
conf
DOI :
10.1109/ICMENS.2009.48
Filename :
5489269
Link To Document :
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