Title :
A Comparison of Principal Component Analysis and Generalized Hebbian Algorithm for Image Compression and Face Recognition
Author :
Rizk, M.R.M. ; Koosha, E.M.
Author_Institution :
Dept. of Electr. Eng., Alexandria Univ.
Abstract :
In this paper we perform image compression and face recognition using principal component analysis (PCA) and the generalized Hebbian algorithm (GHA) which is one of the PCA techniques involving neural network. By implementing the PCA and GHA algorithms for image compression we found that PCA gives better compression ratio to the image than GHA and as for face recognition we found that GHA gives more recognition rate than PCA
Keywords :
data compression; face recognition; image coding; neural nets; principal component analysis; face recognition; generalized Hebbian algorithm; image compression; neural network; principal component analysis; Covariance matrix; Data mining; Eigenvalues and eigenfunctions; Face recognition; Image coding; Image recognition; Karhunen-Loeve transforms; Neural networks; Principal component analysis; Symmetric matrices;
Conference_Titel :
Computer Engineering and Systems, The 2006 International Conference on
Conference_Location :
Cairo
Print_ISBN :
1-4244-0271-9
Electronic_ISBN :
1-4244-0272-7
DOI :
10.1109/ICCES.2006.320450
