Supporting fingerprint identification assessments using a skin stretch model — A preliminary study

Rebecca Lee, Bruce Comber, Joshua Abraham, Michael WAGNER, Chris Lennard, Xanthe Spindler, Claude Roux

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    To support fingerprint expert opinion, this research proposes an approach that combines subjective human analysis (as currently applied by fingerprint practitioners) with a statistical test of the result. This approach relies on the hypothesis that there are limits to the distortion caused by skin stretch. Such limits can be modelled by applying a multivariate normal probability density function to the distances and angle formed by a marked ridge characteristic and the two closest neighbouring minutiae. This study presents a model tested on 5 donors in total. The “expected range” of distortion in a within-source comparison using 10 minutiae was determined and compared to between-source comparisons. The expected range of log probability densities for within-source comparisons marked with 10 minutiae was determined to be from -33.4 to -60.0, with all between-source data falling outside this range, between -83 and -305. These results suggest that the proposed generated metric could be a powerful tool for the assessment of fingerprint expert opinion in operational casework.
    Original languageEnglish
    Pages (from-to)41-49
    Number of pages9
    JournalForensic Science International
    Volume272
    DOIs
    Publication statusPublished - 2017

    Fingerprint

    Dermatoglyphics
    Expert Testimony
    Skin
    Accidental Falls
    Information Storage and Retrieval
    Research

    Cite this

    Lee, Rebecca ; Comber, Bruce ; Abraham, Joshua ; WAGNER, Michael ; Lennard, Chris ; Spindler, Xanthe ; Roux, Claude. / Supporting fingerprint identification assessments using a skin stretch model — A preliminary study. In: Forensic Science International. 2017 ; Vol. 272. pp. 41-49.
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    abstract = "To support fingerprint expert opinion, this research proposes an approach that combines subjective human analysis (as currently applied by fingerprint practitioners) with a statistical test of the result. This approach relies on the hypothesis that there are limits to the distortion caused by skin stretch. Such limits can be modelled by applying a multivariate normal probability density function to the distances and angle formed by a marked ridge characteristic and the two closest neighbouring minutiae. This study presents a model tested on 5 donors in total. The “expected range” of distortion in a within-source comparison using 10 minutiae was determined and compared to between-source comparisons. The expected range of log probability densities for within-source comparisons marked with 10 minutiae was determined to be from -33.4 to -60.0, with all between-source data falling outside this range, between -83 and -305. These results suggest that the proposed generated metric could be a powerful tool for the assessment of fingerprint expert opinion in operational casework.",
    author = "Rebecca Lee and Bruce Comber and Joshua Abraham and Michael WAGNER and Chris Lennard and Xanthe Spindler and Claude Roux",
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    Supporting fingerprint identification assessments using a skin stretch model — A preliminary study. / Lee, Rebecca; Comber, Bruce; Abraham, Joshua; WAGNER, Michael; Lennard, Chris; Spindler, Xanthe; Roux, Claude.

    In: Forensic Science International, Vol. 272, 2017, p. 41-49.

    Research output: Contribution to journalArticle

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    AU - Lee, Rebecca

    AU - Comber, Bruce

    AU - Abraham, Joshua

    AU - WAGNER, Michael

    AU - Lennard, Chris

    AU - Spindler, Xanthe

    AU - Roux, Claude

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    AB - To support fingerprint expert opinion, this research proposes an approach that combines subjective human analysis (as currently applied by fingerprint practitioners) with a statistical test of the result. This approach relies on the hypothesis that there are limits to the distortion caused by skin stretch. Such limits can be modelled by applying a multivariate normal probability density function to the distances and angle formed by a marked ridge characteristic and the two closest neighbouring minutiae. This study presents a model tested on 5 donors in total. The “expected range” of distortion in a within-source comparison using 10 minutiae was determined and compared to between-source comparisons. The expected range of log probability densities for within-source comparisons marked with 10 minutiae was determined to be from -33.4 to -60.0, with all between-source data falling outside this range, between -83 and -305. These results suggest that the proposed generated metric could be a powerful tool for the assessment of fingerprint expert opinion in operational casework.

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