Cart (Loading....) | Create Account
Close category search window
 

Recognition of Faces Using Improved Principal Component Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Gomathi, E. ; Dept. of ECE, Karpagam Coll. of Eng., Coimbatore, India ; Baskaran, K.

Face recognition has been an important issue in computer vision and pattern recognition over the last several decades. While a human can recognize faces easily, automated face recognition remains a great challenge in computer-based automated recognition research. One difficulty in face recognition is how to handle the variations in expression, pose, and illumination when only a limited number of training samples are available. In this paper, an Improved Principal Component Analysis (IPCA) is proposed for face recognition. Initially the eigenspace is created with eigenvalues and eigenvectors. From this space, the eigenfaces are constructed, and the most relevant eigenfaces have been selected using IPCA. With these eigenfaces, the input images are be classified based on Euclidian distance. The proposed method was tested on ORL face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

Published in:

Machine Learning and Computing (ICMLC), 2010 Second International Conference on

Date of Conference:

9-11 Feb. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.