Influence of the datasets size on the stability of the LR in the lower region of the within source distribution

Rudolf Haraksim, Didier Meuwly

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

This article focuses on the statistical evaluation of the fingermark evidence using the likelihood ratio (LR) approach. It studies the influence of the quantity of data used to model the within (WS) and between (BS) source variability. The LR system built for the experiment uses an Automated Fingerprint Identification System (AFIS) feature extraction and comparison algorithm, fingermark and fingerprint datasets coupled with a generative approach for modeling the WS and BS variability. This article concentrates on the computation of LRs of the same source in the lower region of the WS distribution. It analyzes the behavior of the LR with an increasing number of entries in the WS datasets while maintaining the constant proportion of the BS dataset in an attempt to estimate the amount of same source scores necessary to achieve consistent LR performance.
Original languageUndefined
Title of host publicationProceedings of Biometric Technologies in Forensic Science, BTFS 2013
Place of PublicationNijmegen
PublisherRadboud University Nijmegen
Pages34-38
Number of pages5
ISBN (Print)2351-9738
Publication statusPublished - Oct 2013

Publication series

NameBiometric Technologies in Forensic Science
PublisherRadboud University Nijmegen
ISSN (Print)2351-9738

Keywords

  • EWI-25377
  • METIS-309696
  • IR-93344
  • Forensic Science

Cite this

Haraksim, R., & Meuwly, D. (2013). Influence of the datasets size on the stability of the LR in the lower region of the within source distribution. In Proceedings of Biometric Technologies in Forensic Science, BTFS 2013 (pp. 34-38). (Biometric Technologies in Forensic Science). Nijmegen: Radboud University Nijmegen.
Haraksim, Rudolf ; Meuwly, Didier. / Influence of the datasets size on the stability of the LR in the lower region of the within source distribution. Proceedings of Biometric Technologies in Forensic Science, BTFS 2013. Nijmegen : Radboud University Nijmegen, 2013. pp. 34-38 (Biometric Technologies in Forensic Science).
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abstract = "This article focuses on the statistical evaluation of the fingermark evidence using the likelihood ratio (LR) approach. It studies the influence of the quantity of data used to model the within (WS) and between (BS) source variability. The LR system built for the experiment uses an Automated Fingerprint Identification System (AFIS) feature extraction and comparison algorithm, fingermark and fingerprint datasets coupled with a generative approach for modeling the WS and BS variability. This article concentrates on the computation of LRs of the same source in the lower region of the WS distribution. It analyzes the behavior of the LR with an increasing number of entries in the WS datasets while maintaining the constant proportion of the BS dataset in an attempt to estimate the amount of same source scores necessary to achieve consistent LR performance.",
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Haraksim, R & Meuwly, D 2013, Influence of the datasets size on the stability of the LR in the lower region of the within source distribution. in Proceedings of Biometric Technologies in Forensic Science, BTFS 2013. Biometric Technologies in Forensic Science, Radboud University Nijmegen, Nijmegen, pp. 34-38.

Influence of the datasets size on the stability of the LR in the lower region of the within source distribution. / Haraksim, Rudolf; Meuwly, Didier.

Proceedings of Biometric Technologies in Forensic Science, BTFS 2013. Nijmegen : Radboud University Nijmegen, 2013. p. 34-38 (Biometric Technologies in Forensic Science).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - This article focuses on the statistical evaluation of the fingermark evidence using the likelihood ratio (LR) approach. It studies the influence of the quantity of data used to model the within (WS) and between (BS) source variability. The LR system built for the experiment uses an Automated Fingerprint Identification System (AFIS) feature extraction and comparison algorithm, fingermark and fingerprint datasets coupled with a generative approach for modeling the WS and BS variability. This article concentrates on the computation of LRs of the same source in the lower region of the WS distribution. It analyzes the behavior of the LR with an increasing number of entries in the WS datasets while maintaining the constant proportion of the BS dataset in an attempt to estimate the amount of same source scores necessary to achieve consistent LR performance.

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Haraksim R, Meuwly D. Influence of the datasets size on the stability of the LR in the lower region of the within source distribution. In Proceedings of Biometric Technologies in Forensic Science, BTFS 2013. Nijmegen: Radboud University Nijmegen. 2013. p. 34-38. (Biometric Technologies in Forensic Science).