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 languageEnglish
    Title of host publicationInformatics Engineering and Information Science
    Subtitle of host publicationInternational Conference, ICIEIS 2011, Kuala Lumpur, Malaysia, November 14-16, 2011. Proceedings, Part II
    EditorsAzizah Abd Manaf, Akram Zeki, Mazdak Zamani, Suriayati Chuprat, Eyas El-Qawasmeh
    Place of PublicationBerlin, Heidelberg
    Number of pages9
    ISBN (Electronic)978-3-642-25453-6
    ISBN (Print)978-3-642-25452-9
    Publication statusPublished - Nov 2011
    EventInternational Conference on Informatics Engineering and Information Science, ICIEIS 2011 - Kuala Lumpur, Malaysia
    Duration: 14 Nov 201116 Nov 2011

    Publication series

    NameCommunications in Computer and Information Science
    ISSN (Print)1865-0929
    ISSN (Electronic)1865-0937


    ConferenceInternational Conference on Informatics Engineering and Information Science, ICIEIS 2011
    Abbreviated titleICIEIS
    CityKuala Lumpur


    • Evidence
    • Bayesian framework
    • EC Grant Agreement nr.: FP7/238803
    • Likelihood ratio
    • SCS-Safety
    • Similarity score


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