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Quantitative Algorithm for the Digital Comparison of Torn Duct

NCJ Number
250661
Author(s)
William Ristenpart; Frederic Tulleners; Alicia Alfter
Date Published
March 2017
Length
55 pages
Annotation
The goal of this research was to minimize human contextual bias in decisions about whether torn duct tape found at a crime scene matches a duct-tape roll found in a suspect's possession by combining digital image analysis and an objective, quantitative algorithm in assessing the likelihood of a match.
Abstract

Researchers performed edge detection and morphological smoothing operations on high-resolution images (1200 dpi) of torn duct tape edges to extract the torn-edge coordinates. The coordinates of a given exemplar and a suspect sample tear were then compared by calculating the sum of square residuals (SSR) of the two sets of coordinates, producing a single quantitative number that represented the "closeness" of the match. The analysis of 11 cohorts of 200 torn pairs yielded 2,200 total pairs with 440,000 quantitative inter-comparisons, showing that SSR values on the order of or less than 105 mm2 have high probability of being a match. In 97 percent of all examined tears, the true match had the lowest observed SSR, with false positive rates ranging from 0.5 percent for some types of hand-torn duct tape to 62 percent for scissors-cut duct tape. This work provides a starting point for quantitative assessment of the likelihood of physical end matching of duct tape without human contextual bias. 13 figures, 4 tables, and 9 references