Roberto Puch-Solis

Computation of likelihood ratios in fingerprint identification for configurations of any number of minutiae.

ABSTRACT: Recent court challenges have highlighted the need for statistical research on fingerprint identification. This paper proposes a model for computing likelihood ratios (LRs) to assess the evidential value of comparisons with any number of minutiæ. The model considers minutiae type, direction and relative spatial relationships. It expands on previous work on three minutiae by adopting a spatial modeling using radial triangulation and a probabilistic distortion model for assessing the numerator of the LR. The model has been tested on a sample of 686 ulnar loops and 204 arches. Features vectors used for statistical analysis have been obtained following a preprocessing step based on Gabor filtering and image processing to extract minutiae data. The metric used to assess similarity between two feature vectors is based on an Euclidean distance measure. Tippett plots and rates of misleading evidence have been used as performance indicators of the model. The model has shown encouraging behavior with low rates of misleading evidence and a LR power of the model increasing significantly with the number of minutiæ. The LRs that it provides are highly indicative of identity of source on a significant proportion of cases, even when considering configurations with few minutiæ. In contrast with previous research, the model, in addition to minutia type and direction, incorporates spatial relationships of minutiæ without introducing probabilistic independence assumptions. The model also accounts for finger distortion.

Computation of Likelihood Ratios in Fingerprint Identification for Configurations of Three Minutiae

ABSTRACT: Recent challenges to fingerprint evidence have brought forward the need for peer‐reviewed scientific publications to support the evidential value assessment of fingerprint. This paper proposes some research directions to gather statistical knowledge of the within‐source and between‐sources variability of configurations of three minutiæ on fingermarks and fingerprints. This paper proposes the use of the likelihood ratio (LR) approach to assess the value of fingerprint evidence. The model explores the statistical contribution of configurations of three minutiae using Tippett plots and related measures to assess the quality of the system. Features vectors used for statistical analysis have been obtained following a preprocessing step based on Gabor filtering and image processing to extract minutia position, type, and direction. Spatial relationships have been coded using Delaunay triangulation. The metric, used to assess similarity between two feature vectors is based on an Euclidean distance measure. The within‐source variability has been estimated using a sample of 216 fingerprints from four fingers (two donors). Between‐sources variability takes advantage of a database of 818 ulnar loops from randomly selected males. The results show that the data‐driven approach adopted here is robust. The magnitude of LRs obtained under the prosecution and defense propositions stresses upon the major evidential contribution that small portions of fingermark, containing three minutiæ, can provide regardless of its position on the general pattern.

Evidential evaluation of DNA profiles using a discrete statistical model implemented in the DNA LiRa software

The high sensitivity of the technology for producing profiles means that it has become routine to produce profiles from relatively small quantities of DNA. The profiles obtained from low template DNA (LTDNA) are affected by several phenomena which must be taken into consideration when interpreting and evaluating this evidence. Furthermore, many of the same phenomena affect profiles from higher amounts of DNA (e.g. where complex mixtures has been revealed). In this article we present a statistical model, which forms the basis of software DNA LiRa, and that is able to calculate likelihood ratios where one to four donors are postulated and for any number of replicates. The model can take into account dropin and allelic dropout for different contributors, template degradation and uncertain allele designations. In this statistical model unknown parameters are treated following the Empirical Bayesian paradigm. The performance of LiRa is tested using examples and the outputs are compared with those generated using two other statistical software packages likeLTD and LRmix. The concept of ban efficiency is introduced as a measure for assessing model sensitivity.

A dropin peak height model

The technology for producing DNA profiles is very sensitive and is able to produce profiles from process negative controls typically consisting of one or two peaks, a phenomenon known as dropin. There are several types of models that implement likelihood ratios for the statistical evaluation of DNA profiles. One of the types is the family of continuous models because they consider continuous peak height/area measurements from the stain profile. Nowadays, there are several continuous models available. The aim of this article is to expose a statistical model for dropin peak heights supported by data, and illustrate its incorporation into a continuous method.

Consideration of the probative value of single donor 15-plex STR profiles in UK populations and its presentation in UK courts

The adoption of new 15 locus STR multiplex systems into UK forensic science would be facilitated by agreed guidelines for reporting the strength of DNA evidence using likelihood ratios. To facilitate such an agreement, we present an analysis of previously published UK allele frequencies for white Caucasian, Afro-Caribbean and Indo-Pakistani populations and investigate their effect on likelihood ratios for single donor profiles. We consider the implication of the five additional loci and suggest a procedure for reporting likelihood ratios for 15-plex STR profiles.

Calculating likelihood ratios for a mixed DNA profile when a contribution from a genetic relative of a suspect is proposed

This technical note describes a practical method for evaluating evidence in the case of a two person conditioned DNA mixture where the defence proposition is that the unknown contributor is genetically related to the suspect. A conditioned mixture is one where the presence of DNA from one of two individuals is accepted by both prosecution and defence. A typical example would be a vaginal swab in an alleged rape case, where the presence of the complainants DNA would be expected and samples have been taken from the complainant and a suspect. Much has been written about the interpretation of such mixtures and the calculation of the conditional genotype probabilities that must be carried out. In general, such treatments assume that the unknown contributor, under the defence proposition, is unrelated to the known individuals. In this paper, we consider the case where the defence proposition is that the unknown contributor is genetically related to the suspect. We describe a method, incorporating a flow chart and reference tables that facilitate manual calculations of the likelihood ratio for several postulated genetic relationships.

Providing scientific guidance on DNA to the judiciary

A series of short documents have been written in response to a request from the UK Judiciary for explanations of research that was commissioned in response to questions they had raised. These related principally to the potential impact of primer binding site mutation (PBSM) but it became clear at an early stage that it was necessary to explain related issues. The three scientific guidance papers (SGPs) that have been prepared thus far are presented in their entirety so that UK scientists may be aware of what has been presented to judges. Suggestions for further work, including possible communication to jurors are discussed.