Citation

Hare E, Hofmann H, Carriquiry A. Ann. Appl. Stat. 2017; 11(4): 2332-2356.

Copyright

(Copyright © 2017, Institute of Mathematical Statistics)

DOI

10.1214/17-AOAS1080

PMID

unavailable

Abstract

In 2009, the National Academy of Sciences published a report questioning the scientific validity of many forensic methods including firearm examination. Firearm examination is a forensic tool used to help the court determine whether two bullets were fired from the same gun barrel. During the firing process, rifling, manufacturing defects, and impurities in the barrel create striation marks on the bullet. Identifying these striation markings in an attempt to match two bullets is one of the primary goals of firearm examination. We propose an automated framework for the analysis of the 3D surface measurements of bullet land impressions, which transcribes the individual characteristics into a set of features that quantify their similarities. This makes identification of matches easier and allows for a quantification of both matches and matchability of barrels. The automatic matching routine we propose manages to (a) correctly identify land impressions (the surface between two bullet groove impressions) with too much damage to be suitable for comparison, and (b) correctly identify all 10,384 land-to-land matches of the James Hamby study (Hamby, Brundage and Thorpe [AFTE Journal 41 (2009) 99-110]).

Language: en

Keywords

3D topological surface measurement; cross-correlation function; data visualization; feature importance; machine learning