Face Recognition Using Eigenfaces Technique

Hazirah, Zakaria (2014) Face Recognition Using Eigenfaces Technique. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 Pages) Face Recognition Using Eigenfaces Technique 24 Pages.pdf - Submitted Version Download (721kB)

Abstract

This project used Viola-Jones algorithm as face detection of person face showing high-success rate and enable to operate together with face recognition as real-time detection. There are some limitation to consider as well as the environment, the size of image and the pose of the person itself. Face recognition concept s is one of the successful and become substantial applications of image analysis and computer vision. Eigenface approach is one of the earliest methods for face recognition, which was developed by M.Turk and A.pentland in 1991[1].It has built based on computerized face-matching process and can be applied for a wide variety of problems such as Biometrics, Information Society, Criminal Identification, Smart Cards, Access Control, etc. The system is to implement a model for a particular face and distinguish it from a large number of stored faces with some real-time variations as well. An algorithm called Principle Component Analysis (PCA) is used for Eigenfaces as a method for face recognition. The process for face recognition involves the given image which formed to the eigenfaces, and the Euclidean distances between the eigenfaces, then, the previously stored eigenfaces are calculated. The smallest Euclidean distance of the eigenfaces resulting the one the person resemble the most. The simulation has done by generating a matlab code using image acquisition tool box. The success rate for the large database has reach up to 94.74%.

Actions (login required)

View Item