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.
|Name||Biometric Technologies in Forensic Science|
|Publisher||Radboud University Nijmegen|
|Conference||Proceedings of Biometric Technologies in Forensic Science, BTFS 2013, Nijmegen|
|Period||1/10/13 → …|
- Forensic Science