Quantifying Information Content in Pattern Evidence

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• Karen Kafadar (University of Virginia)
• Friday 11 November 2016, 11:30-12:00
• Seminar Room 1, Newton Institute.

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FOSW03 - Statistical modelling of scientific evidence

The first step in the ACE -V process for comparing fingerprints is the “Analysis” phase, where the latent print under investigation is subjectively assessed for its “suitability” (e.g., clarity and relevance of features and minutiae). Several proposals have been offered for objectively characterizing the “quality” of a latent print. The goal of such an objective assessment is to relate the “quality metric” (which may be a vector of quality scores) to the accuracy of the call (correct ID or correct exclusion), so that latent print examiners (LPEs) can decide immediately whether to proceed with the other steps of ACE -V. We describe some of these proposals that attempt to quantify the “information content” of a latent print or of its individual features (“minutiae”) and describe initial efforts aimed at assessing their association with accuracy, using first NIST 's public SD27a latent fingerprint database containing prints judged by “experts” as “good,” “bad,” or “ugly.” One proposed metric, based on gradients to determine the clarity of the minutiae, correlates well with the general classification and thus can serve as an objective, vs subjective, measure of information content. 

This talk is part of the Isaac Newton Institute Seminar Series series.

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