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                            Library & Multimedia
 Textural feature based face recognition for single training images
NCJ Number
              305862

Author(s)
          Richa Singh;
                        Mayank Vatsa;
                        Afzel Noore
Date Published

2005
Length
              2 pages
Annotation
              This article proposes a novel face-recognition algorithm that uses a single training face image.
Abstract
              The algorithm is based on textural features extracted using the 2D log Gabor wavelet. These features are encoded into a binary pattern to form a face template which is used for matching. Experimental results show that on the color FERET database the accuracy of the proposed algorithm is higher than the local feature analysis (LFA) and correlation filter (CF) based face recognition algorithms even when the number of training images is reduced to one. In comparison with recent single training image-based face recognition algorithms, the proposed 2D log Gabor wavelet-based algorithm shows an improvement of more than 3% in accuracy. (Published Abstract Provided)
      
  
          Additional Details
Grant Number(s)
        2003-RC-CX-K001


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        Forensic Science Initiative 2003
    
  
  
Date Published: January 1, 2005
    
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