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Springer, Lecture Notes in Computer Science, p. 1080-1089, 2005

DOI: 10.1007/11527923_112

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Between-Source Modelling for Likelihood Ratio Computation in Forensic Biometric Recognition

This paper is available in a repository.
This paper is available in a repository.

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Abstract

In this paper, the use of biometric systems in forensic ap- plications is reviewed. Main differences between the aim of commercial biometric systems and forensic reporting are highlighted, showing that commercial biometric systems are not suited to directly report results to a court of law. We propose the use of a Bayesian approach for foren- sic reporting, in which the forensic scientist has to assess a meaningful value, in the form of a likelihood ratio (LR). This value assist the court in their decision making in a clear way, and can be computed using scores coming from any biometric system, with independence of the biometric discipline. LR computation in biometric systems is reviewed, and sta- tistical assumptions regarding estimations involved in the process are addressed. The paper is focused in handling small sample size effects in such estimations, presenting novel experiments using a fingerprint and a voice biometric system.