Fast Face Recognition Using Eigen Faces

Abstract

Face is a typical multidimensional structure and needs good computational analysis for recognition. Our approach signifies face recognition as a two-dimensional problem. In this approach, face recognization is done by Principal Component Analysis (PCA). Face images are faced onto a space that encodes best difference among known face images. The face space is created by eigenface methods which are eigenvectors of the set of faces, which may not link to general facial features such as eyes, nose, and lips. The eigenface method uses the PCA for recognition of the images. The system performs by facing pre-extracted face image onto a set of face space that shows significant difference among known face images. Face will be categorized as known or unknown face after imitating it with the present database.