期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2013
卷号：4
期号：6
页码：839-843
出版社：TechScience Publications
摘要：In this paper, we present a novel method to gender classification using a new simple feature extraction which extracts geometric features such as distance between eyebrow to eye, eyebrow to nose top, nose top to mouth, eye to mouth, left eye to right eye, width of nose, width of mouth. First to extract these features by using Viola Jones algorithm and then apply Artificial Neural Network. The features set is applied to three different applications: face recognition, facial expressions recognition and gender classification, which produced the reasonable results in all database. We described two phases such as feature extraction phase and classification phase. These features provide input to trained neural networks. The neural networks have been proposed for classification purpose. The networks have been trained to produce value 1 for male and 0 for female. Output of these neural network determines the gender of the person. The results using a training database of 100 male and 100 female images from CIPM institute
