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Establishing Likelihood Ratios for Patterned Garment Comparisons from Seam Measurement Data,

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Abstract

It is often challenging to ascribe an objective measure of confidence for identifications based on surveillance imagery from a crime scene. The present work seeks to address this deficiency in the case of garment comparison evidence by developing a quantitative method for establishing a conservative lower bound on the likelihood ratio (LR) for identifications involving patterned garments. The method is based on statistical analysis of pattern offset measurements taken from a sample of garments of the same type (manufacturer, style, and size) as the seized evidence. The developed analysis framework was demonstrated on different types of garments over a range of modeled surveillance imaging scenarios with variable image quality; the lower bounds on the LRs ranged from approximately 10–1 to over 400–1. The statistical model was tested and validated through a large‐scale empirical study involving both simulated and human observer‐performed garment comparisons.
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Document Type: Research Article

Publication date: May 1, 2013

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