Gender estimation based on facial image

Abstract

Although gender classification has attracted much attention in psychological literature, relatively few machine vision methods has been proposed. However it has been extensively studied in the context of surveillance applications and biometrics. This project is mainly concern with gender classification using purely image processing technique. The way of doing this is by extracting the differences between male and female facial features. Obviously the classification base on a single feature is not adequate since humans share many facial properties even within different gender group. So multilayer processing is needed. This project is working as expected with specified scope of project. Although not many varieties of facial images have been considered like colored hair the basic techniques should be just the same. The proposed methods can be extended to various purposes especially in speeding up the processing time in database searching. The refinement of this project in other hand can lead to more accurate and reliable result by considering other facial properties like eyes, nose and eyebrows.