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Reproducibility of Automated Bullet Matching Scores Using High-Resolution 3D LEA Scans

Conference/Workshop:
AFTE Annual Training Seminar
Published: 2019
Primary Author: Kiegan Rice
Research Area: Firearms and Toolmarks

Development of automated bullet matching algorithms based on 3D scans of land engraved areas (LEAs) has become a prominent area of research in recent years. However, automated methods rely heavily on the data gathered in 3D scans. The high-resolution 3D scan data can vary depending on which operator scans the LEA or which microscope it is scanned on. It is therefore important to study the reliability of automated approaches and the potential impact the scanning process can have on accuracy. In order for a method to be reliable, pairwise matching scores for two bullet LEAs need to be similar regardless of which operator or machine gathers the data. A repeatability and reproducibility (R&R) study to evaluate sources of variability was completed in order to address this issue. R&R studies are used to quantify two aspects of data collection: the repeatability of measurements when taken under the same environmental conditions, and the reproducibility of measurements when taken under different environmental conditions. Nine bullets, three each from three different barrels, were repeatedly scanned at Iowa State University’s High Resolution Microscopy Lab. Five microscope operators captured scans of each bullet on two Sensofar Confocal Light Microscopes, restaging each bullet on the microscope for each new repetition.This presentation will contain results from the study, addressing the observed differences on extracted LEA signatures as well as the impact on accuracy of an automated matching algorithm proposed by Hare, Hofmann, and Carriquiry of the Center for Statistics and Applications in Forensic Evidence (CSAFE). Pairwise matching scores for LEAs are minimally affected by operator. The largest sources of variability in pairwise scores are individual bullet characteristics such as breakoff or pitting.

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