Gender Classification using Geometric Facial Features

Abstract

Abstract— Image processing is a field in which biometric traits such as Face, voice, lip movements, hand geometry, odor, gait, iris, retina, fingerprint etc. are important for recognition. Face is the most important biometric trait for recognition because face is easily approachable biometric trait there is no need of attention from human being for face recognition. Human face classification is the challenging task for machine. In this project minimum distance classifier is used with Principal Component Analysis based gender classification. Database of 100 images (50 male and 50 female face images) is used for the face recognition and classification. Original face image database is used for the gender classification. It is observed that gender classification accuracy of our project is 97%. The proposed paper is nothing but sequential steps of gender classification system.