Citation

Warren EM, Sheets HD. J. Forensic Sci. 2018; 63(2): 431-439.

Affiliation

Department of Physics, Canisius College, 2001 Main Street, Buffalo, NY, 14208.

Copyright

(Copyright © 2018, American Society for Testing and Materials, Publisher John Wiley and Sons)

DOI

10.1111/1556-4029.13529

PMID

28464307

Abstract

While type determination on bullets has been performed for over a century, type determination on cartridge cases is often overlooked. Presented here is an example of type determination of ejector marks on cartridge cases from Glock and Smith & Wesson Sigma series pistols using Naïve Bayes and Random Forest classification methods. The shapes of ejector marks were captured from images of test-fired cartridge cases and subjected to multivariate analysis. Naïve Bayes and Random Forest methods were used to assign the ejector shapes to the correct class of firearm with success rates as high as 98%. This method is easily implemented with equipment already available in crime laboratories and can serve as an investigative lead in the form of a list of firearms that could have fired the evidence. Paired with the FBI's General Rifling Characteristics (GRC) database, this could be an invaluable resource for firearm evidence at crime scenes.

© 2017 American Academy of Forensic Sciences.

Language: en

Keywords

Glock; Naïve Bayes classification; Smith & Wesson Sigma; ejector marks; forensic science; morphometrics