Face Recognition Using Principal Component Analysis and Wavelet Packet Decomposition
Volume 15, Issue 2 (2004), pp. 243–250
Pub. online: 1 January 2004
Type: Research Article
Received
1 October 2003
1 October 2003
Published
1 January 2004
1 January 2004
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%).