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Towards Automatic Forensic Face Recognition

  • Tauseef Ali
  • Luuk Spreeuwers
  • Raymond Veldhuis
Part of the Communications in Computer and Information Science book series (CCIS, volume 252)

Abstract

In this paper we present a methodology and experimental results for evidence evaluation in the context of forensic face recognition. In forensic applications, the matching score (hereafter referred to as similarity score) from a biometric system must be represented as a Likelihood Ratio (LR). In our experiments we consider the face recognition system as a ‘black box’ and compute LR from similarity scores. The proposed approach is in accordance with the Bayesian framework where the duty of a forensic scientist is to compute LR from biometric evidence which is then incorporated with prior knowledge of the case by the judge or jury. In our experiments we use a total of 2878 images of 100 subjects from two different databases. Our experimental results prove the feasibility of our approach to reach a LR value given an image of a suspect face and questioned face. In addition, we compare the performance of two biometric face recognition systems in forensic casework.

Keywords

LR Evidence Similarity score Bayesian framework 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tauseef Ali
    • 1
  • Luuk Spreeuwers
    • 1
  • Raymond Veldhuis
    • 1
  1. 1.Faculty of Electrical Engineering, Mathematics and Computer ScienceUniversity of TwenteThe Netherlands

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