Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | Proceedings of Biometric Technologies in Forensic Science, BTFS 2013 |
| Place of Publication | Nijmegen |
| Publisher | Radboud University Nijmegen |
| Pages | 34-38 |
| Number of pages | 5 |
| ISBN (Print) | 2351-9738 |
| Publication status | Published - Oct 2013 |
Publication series
| Name | Biometric Technologies in Forensic Science |
|---|---|
| Publisher | Radboud University Nijmegen |
| ISSN (Print) | 2351-9738 |
Keywords
- EWI-25377
- METIS-309696
- IR-93344
- Forensic Science
Cite this
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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 proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Influence of the datasets size on the stability of the LR in the lower region of the within source distribution
AU - Haraksim, Rudolf
AU - Meuwly, Didier
PY - 2013/10
Y1 - 2013/10
N2 - 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.
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.
KW - EWI-25377
KW - METIS-309696
KW - IR-93344
KW - Forensic Science
M3 - Conference contribution
SN - 2351-9738
T3 - Biometric Technologies in Forensic Science
SP - 34
EP - 38
BT - Proceedings of Biometric Technologies in Forensic Science, BTFS 2013
PB - Radboud University Nijmegen
CY - Nijmegen
ER -