Subscribe Now Subscribe Today
Science Alert
 
FOLLOW US:     Facebook     Twitter
Blue
   
Curve Top
Information Technology Journal
  Year: 2004 | Volume: 3 | Issue: 3 | Page No.: 290-295
DOI: 10.3923/itj.2004.290.295
Principal Component Analysis of Directional Images for Face Recognition
Mohammad A.U. Khan, Muhammad Khalid Khan , Muhammad Aurangzeb Khan , Muhammad Talal Ibrahim , Muhammad Kamran Ahmed and Jahanzeb Afzal Baig

Abstract:
This study addresses new face recognition method based on Principal Component Analysis (PCA) and Directional Filter Bank (DFB) responses. Our method consists of two parts. One is the creation of directional images using DFB from the original face image. The other is transforming the directional images into eigenspace by PCA, which is able to optimally classify individual facial representations. PCA analysis is primarily used as a dimensionality reduction technique with least consideration to the recognition aspect. The basic idea of combining PCA and DFB is to provide PCA with some recognition ability. In our system recognition ability of the PCA is enhanced by providing directional images as inputs. The experiment results showed the remarkable improvement of recognition rate of 21.25% in Olivetti data set.
 [Fulltext PDF]   [Fulltext HTML]   [XML: Abstract + References]   [References]   [View Citation]  [Report Citation]
 RELATED ARTICLES:
  •    AAAM-face Based Authentication System for Information Security
  •    Illumination Normalization using Eimad-housam Technique
  •    Face Detection Based on Graph Structure and Neural Networks
  •    Background Interference Elimination in Wound Infection Detection by Electronic Nose Based on Reference Vector-based Independent Component Analysis
How to cite this article:

Mohammad A.U. Khan, Muhammad Khalid Khan , Muhammad Aurangzeb Khan , Muhammad Talal Ibrahim , Muhammad Kamran Ahmed and Jahanzeb Afzal Baig , 2004. Principal Component Analysis of Directional Images for Face Recognition. Information Technology Journal, 3: 290-295.

DOI: 10.3923/itj.2004.290.295

URL: https://scialert.net/abstract/?doi=itj.2004.290.295

 
COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 

Curve Bottom