Integration of Pore Features into the Evaluation of Fingerprint Evidence

Fingerprint practitioners rely on level 3 features to make decisions in relation to the source of an unknown friction ridge skin impression. This research proposes to assess the strength of evidence associated with pores when shown in (dis)agreement between a mark and a reference print. Based upon an algorithm designed to automatically detect pores, a metric is defined in order to compare different impressions. From this metric, the weight of the findings is quantified using a likelihood ratio. The results obtained on four configurations and 54 donors show the significant contribution of the pore features and translate into statistical terms what latent fingerprint examiners have developed holistically through experience. The system provides LRs that are indicative of the true state under both the prosecution and the defense propositions. Not only such a system brings transparency regarding the weight to assign to such features, but also forces a discussion in relation to the risks of such a model to mislead.