Premium
Establishing Likelihood Ratios for Patterned Garment Comparisons from Seam Measurement Data ,
Author(s) -
Johnson D. B.,
Perlin Victor E.,
Rohde Mitchell M.,
Thomas Alice C.,
Luu Cuong Q.,
Chang Jennifer
Publication year - 2013
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.12125
Subject(s) - offset (computer science) , computer science , observer (physics) , clothing , statistics , range (aeronautics) , data mining , artificial intelligence , mathematics , engineering , geography , physics , archaeology , quantum mechanics , aerospace engineering , programming language
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.