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                            Library & Multimedia
 Robust hand geometry measurements for person identification using active appearance models
NCJ Number
              305648

Author(s)
          Ralph Gross;
                        Yiheng Li;
                        Latanya Sweeney;
                        Xiaoqian Jiang;
                        Wanhong Xu;
                        Daniel Yurovsky
Date Published

2007
Length
              6 pages
Annotation
              This paper introduces a novel approach to hand geometry-based identification.
Abstract
              The increased demand for tighter border and building security has renewed public interest in biometric identification and verification systems. With fingerprint recognition being socially stigmatized, hand geometry-based recognizers have emerged as niche solutions; however, systems currently available in the marketplace require direct contact with the device, raising, among other issues, significant hygiene concerns. The proposed method employs Active Appearance Models to track the hand inside the capture device and to extract geometry features for identification. The AAM fitting algorithm runs faster than real-time, enabling robust system performance. In experiments on a small-scale database of hand images, the accuracy of the authors’ system exceeds 90%, using as little as five features. (Publisher abstract provided)
      
  
          Additional Details
Grant Number(s)
        2005-IJ-CX-K046


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        HandShot ID: A Fast 3-D Imaging System for Capturing Fingerprints, Palm Prints and Hand Geometry
    
  
  
Date Published: January 1, 2007
    
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        Biometrics
        Fingerprints
        Palm prints
        Pattern evidence



  
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