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Using Spatial, Temporal and Evidence-Status Data to Improve Ballistic Imaging Performance

NCJ Number
246547
Journal
Journal of Forensic Sciences Volume: 59 Issue: 1 Dated: January 2014 Pages: 103-111
Author(s)
Yan Yang; Avi Koffman B.Sc.; Gil Hocherman M.Sc.; Lawrence M. Wein Ph.D.
Date Published
January 2014
Length
9 pages
Annotation
Firearms identification imaging systems help solve crimes by comparing newly acquired images of cartridge casings or bullets to a database of images obtained from past crime scenes.
Abstract
Firearms identification imaging systems help solve crimes by comparing newly acquired images of cartridge casings or bullets to a database of images obtained from past crime scenes. We formulate an optimization problem that bases its matching decisions not only on the similarity between pairs of images, but also on the time and spatial location of each new acquisition and each database entry. The objective is to maximize the detection probability subject to a constraint on the false positive rate. We use data on all cartridge casings matches detected in Israel during 2006-2008 to estimate most of the model parameters. We estimate matching accuracy from two different studies and predict that the optimal use of extraneous information would increase the detection probability from 0.931 to 0.987 and from 0.707 to 0.844, respectively. These improvements are achieved by favoring pairs of images that are closer together in space and time. Abstract published by arrangement with Wiley.