Face Recognition Using Principal Component Analysis and Wavelet Packet Decomposition

Authors:
Vytautas Perlibakas
Affiliations:
Image Processing and Analysis Laboratory, Kaunas University of Technology, Studentų 56-305, 51424 Kaunas, Lithuania, e-mail: vperlib@mmlab.ktu.lt
Venue:
Informatica
Year:
2004

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Abstract

In this article we propose a novel Wavelet Packet Decomposition(WPD)-based modification of the classical Principal ComponentAnalysis (PCA)-based face recognition method. The proposedmodification allows to use PCA-based face recognition with a largenumber of training images and perform training much faster thanusing the traditional PCA-based method. The proposed method wastested with a database containing photographies of 423 persons andachieved 82-89% first one recognition rate. These results are closeto that achieved by the classical PCA-based method (83-90%).