Biometric Identification in Forensic Cases According to the Bayesian Approach
Abstract
On the one hand, commercial biometric systems and forensic identification require different approaches in order to evaluate system outputs. On the other hand, bayesian approach for evidence analysis and forensic reporting perfectly suits the needs of the court and the forensic scientist. Inside this bayesian framework, any biometric system can be adapted to provide its results in the form of likelihood ratios (LR) (being so converted in a forensic identification system), and performance of the forensic system can be then assessed according to the bayesian approach. We will focus on a specific biometric characteristic, showing how forensic speaker recognition can be reported by means of bayesian technique. Results including NIST-Ahumada and providing LR scores in the form of Tippet plots (and compared with DET plots) will be finally presented.
Cite
Text
Gonzalez-Rodriguez et al. "Biometric Identification in Forensic Cases According to the Bayesian Approach." European Conference on Computer Vision, 2002. doi:10.1007/3-540-47917-1_18Markdown
[Gonzalez-Rodriguez et al. "Biometric Identification in Forensic Cases According to the Bayesian Approach." European Conference on Computer Vision, 2002.](https://mlanthology.org/eccv/2002/gonzalezrodriguez2002eccv-biometric/) doi:10.1007/3-540-47917-1_18BibTeX
@inproceedings{gonzalezrodriguez2002eccv-biometric,
title = {{Biometric Identification in Forensic Cases According to the Bayesian Approach}},
author = {Gonzalez-Rodriguez, Joaquin and Fiérrez-Aguilar, Julian and Ortega-Garcia, Javier and Lucena-Molina, Jose Juan},
booktitle = {European Conference on Computer Vision},
year = {2002},
pages = {177-185},
doi = {10.1007/3-540-47917-1_18},
url = {https://mlanthology.org/eccv/2002/gonzalezrodriguez2002eccv-biometric/}
}