期刊名称：BVICAM's International Journal of Information Technology
印刷版ISSN：0973-5658
出版年度：2016
卷号：8
期号：2
语种：English
出版社：Bharati Vidyapeeth's Institute of Computer Applications and Management
摘要：An individual face reveals an array of information that can be age, gender or identity. The features play an important task in the estimation of age for a given person, just by looking at the face. In this research, the work is to design a model which classifies age with respect to features taken out from individual facial images by means of Neural Network (NN). In recent years, Artificial Neural Network (ANN) has been extensively used as a means for solving many decision making problems. In this paper for classifying age group a feed forward propagation neural networks is constructed from gray-scale facial images. Age groups are classified in four groups, including babies, young, middle?aged, and adults, applicable in the classification method. The course of action of the system is partitioned into three segments: locality, feature extraction, and age classification. The global features used to distinguish child from middle aged and adults is based on the ratios computed using the eyes, nose, mouth, chin, virtual-top of the head and the sides of the face as those features.
关键词：Index Terms – Age determination;Facial Feature parameter; Neural Networks.
