期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：12
页码：1-8
出版社：Science and Information Society (SAI)
摘要：Automatic verification and identification of face
from facial image to obtain good accuracy with huge dataset of
training and testing to using face attributes from images is still
challengeable. Hence proposing efficient and accurate facial
image identification and classification based of facial attributes is
important task. The prediction from human face image is much
complex. The proposed research work for automatic gender, age
and race classification is based on facial features and
Convolutional Neural Network (CNN). The proposed study uses
the physical appearance of human face to predict age, gender
and race. The proposed methodology consists of three sub
systems, Gender, Ageing and Race. Therefore different feature
are extracted for every sub system. These features are extracted
by using Primary, Secondary features, Face Angle, Wrinkle
Analysis, LBP and WLD. The accuracy of classification is based
on these features. CNN used to classify by using these features.
The proposed study has been evaluated and tested on large
database MORPH II and UTKF. The performance of proposed
system is compared with state of art techniques.
