Towards automatic forensic face recognition

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    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.
    Original languageUndefined
    Title of host publicationInternational Conference on Informatics Engineering and Information Science (ICIEIS 2011)
    Place of PublicationBerlin Heidelberg
    Number of pages9
    ISBN (Print)1865-0929
    Publication statusPublished - Nov 2011

    Publication series

    NameCommunications in Computer and Information Science
    PublisherSpringer Verlag
    ISSN (Print)1865-0929


    • IR-79191
    • METIS-284929
    • Evidence
    • Bayesian framework
    • EC Grant Agreement nr.: FP7/238803
    • Likelihood Ratio
    • SCS-Safety
    • EWI-21053
    • Similarity score

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