TY  - JOUR
T1  - An Efficient Face Feature selection Based on Principle Component Analysis and Genetic
Algorithm
AU - Jasim Mosa, Safaa 
JO  - Asian Journal of Information Technology
VL  - 18
IS  - 6
SP  - 160
EP  - 163
PY  - 2019
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2019.160.163
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2019.160.163
KW  - Feature extraction
KW  -PCA
KW  -GA
KW  -SVM
KW  -neural network
KW  -technique
AB  - The number of features in the face recognition
has an important impact in the recognition stage. Hence,
such important issue in the face recognition methods need
to be solved by choosing accurate features. Here, a new
face feature extraction method with optimal features
extraction via. PCA and Genetic algorithm techniques is
proposed. The proposed method primarily performs
features extraction using PCA and the Genetic algorithm
is used to obtain the optimal features. The optimal
features from PCA+GA is used efficiently to perform the
face recognition process. To validate the proposed feature
selection mechanism, the neural network Feed forward
back propagation neural network has been used for the
recognition purpose. The human face dataset called
CASIA is used to examine the performance of our
proposed PCA+GA technique. The results showed the
proposed method is very effective in choosing the optimal
features and has been reflected that in the recognition
process.
ER  -