DocumentCode :
3247070
Title :
Face Recognition by PCA Technique
Author :
Patil, A.M. ; Kolhe, Satish R. ; Patil, Pradeep M.
Author_Institution :
Dept. of Electron. & Telecommun. Eng., J.T.M. Coll. of Eng., Faizpur, India
fYear :
2009
fDate :
16-18 Dec. 2009
Firstpage :
192
Lastpage :
195
Abstract :
Face recognition is one of the most active research areas in computer vision and pattern recognition with practical applications. This work proposes an appearance based eigenface technique. PCA is used in extracting the relevant information in human faces. In this method the eigenvectors of the set of training images are calculated which define the face space. Face images are projected on to the face space which encodes the variation among known face images. These encoded variations are used for recognition. Experiments are carried on IndianFace Database; the obtained recognition rate is 92.30%. The same training set is tested with nonface database.
Keywords :
eigenvalues and eigenfunctions; face recognition; principal component analysis; PCA technique; computer vision; eigenface technique; eigenvectors; face recognition; pattern recognition; Application software; Computer vision; Data mining; Face detection; Face recognition; Humans; Image databases; Pattern recognition; Principal component analysis; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Trends in Engineering and Technology (ICETET), 2009 2nd International Conference on
Conference_Location :
Nagpur
Print_ISBN :
978-1-4244-5250-7
Electronic_ISBN :
978-0-7695-3884-6
Type :
conf
DOI :
10.1109/ICETET.2009.99
Filename :
5395405
Link To Document :
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