Face Recognition Using Principal Component Analysis and Wavelet Packet Decomposition

Article type: Research Article

Authors: Perlibakas, Vytautas

Affiliations: Image Processing and Analysis Laboratory, Kaunas University of Technology, Studentų 56–305, 51424 Kaunas, Lithuania, e‐mail: [email protected]

Abstract: In this article we propose a novel Wavelet Packet Decomposition (WPD)‐based modification of the classical Principal Component Analysis (PCA)‐based face recognition method. The proposed modification allows to use PCA‐based face recognition with a large number of training images and perform training much faster than using the traditional PCA‐based method. The proposed method was tested with a database containing photographies of 423 persons and achieved 82–89% first one recognition rate. These results are close to that achieved by the classical PCA‐based method (83–90%).

Keywords: face recognition, PCA, Wavelet Packet Decomposition, WPD

Journal: Informatica, vol. 15, no. 2, pp. 243-250, 2004