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Face Recognition Using Principal Component Analysis and Wavelet Packet Decomposition
Volume 15, Issue 2 (2004), pp. 243–250
Vytautas Perlibakas  

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https://doi.org/10.15388/Informatica.2004.057
Pub. online: 1 January 2004      Type: Research Article     

Received
1 October 2003
Published
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%).

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Keywords
face recognition PCA Wavelet Packet Decomposition WPD

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INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
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