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

Face recognition algorithm using wavelet decomposition and Support Vector Machines

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.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)
Wei Wang ; Inf. Sci. & Intell. Syst., Univ. of Tokushima, Tokushima, Japan ; Xiang-yu Sun ; Karungaru, S. ; Terada, K.

Face recognition algorithm is a very promising technique in biometric authentication. However, the recognition precision can be affected by many factors, such as feature extraction method and classifier selection. In this paper, a novel algorithm for face recognition is presented according to the advances of the wavelet decomposition technique and the Support Vector Machines (SVM) model. The extracted features from human images by wavelet decomposition are less sensitive to facial expression variation. As a classifier, SVM provides high generation performance without transcendental knowledge. First, we detect the face region using an improved AdaBoost algorithm. Second, we extract the appropriate features of the face by wavelet decomposition, and compose the face feature vectors as input to SVM. Third, we train the SVM model by the face feature vectors, and then use the trained SVM model to classify the human face. In the training process, three different kernel functions are adopted: Radial basis function, Polynomial and Linear kernel function. Finally, we present a face recognition system that can achieve high recognition precision and fast recognition speed in practice. Experimental results indicate that the proposed method can achieve recognition precision of 96.78 percent based on 96 persons in Ren-FEdb database that is higher than other approaches.

Published in:

Optomechatronic Technologies (ISOT), 2012 International Symposium on

Date of Conference:

29-31 Oct. 2012

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.