Volume 63, Issue 2 pp. 440-448
Paper

A Fully Automatic Method for Comparing Cartridge Case Images,

Xiao Hui Tai M.Stats.

Corresponding Author

Xiao Hui Tai M.Stats.

Department of Statistics, Carnegie Mellon University, Baker Hall 132, Pittsburgh, PA, 15213

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Xiao Hui Tai, M.Stats.

Department of Statistics

Carnegie Mellon University

Baker Hall 132

Pittsburgh

PA 15213

E-mail: [email protected]

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William F. Eddy Ph.D.

William F. Eddy Ph.D.

Department of Statistics, Carnegie Mellon University, Baker Hall 132, Pittsburgh, PA, 15213

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First published: 10 July 2017
Citations: 20
Presented at the Forensics @ NIST 2016 Conference, November 8-9, 2016, in Gaithersburg, MD; and at the 48th Annual Training Seminar of the Association of Firearm and Tool Mark Examiners (AFTE), May 14-19, 2017, in Denver, CO.
Partially funded by the Center for Statistics and Applications in Forensic Evidence (CSAFE) through Cooperative Agreement #70NANB15H176 between NIST and Iowa State University, which includes activities carried out at Carnegie Mellon University, University of California Irvine, and University of Virginia.

Abstract

When a gun is fired, it leaves marks on cartridge cases that are thought to be unique to the gun. In current practice, firearms examiners inspect cartridge cases for “sufficient agreement,” in which case they conclude that they come from the same gun, testifying in courts as such. A 2016 President's Council of Advisors on Science and Technology report questioned the scientific validity of such analysis (President's Committee of Advisors on Science and Technology, Washington, DC, Executive Office of the President). One recommendation was to convert firearms analysis to an objective method. We propose a fully automated, open-source method for comparing breechface marks on cartridge cases using 2D optical images. We improve on existing methodology by automating the selection of marks, and removing the effects of circular symmetry. We propose an empirical computation of a “random match probability” given a known database, which can be used to quantify the weight of evidence. We demonstrate an improvement in accuracy on images from controlled test fires.

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