Novel imaging solution to quantify, evaluate and compare gunshot residue patterns

Kusluski, MA, Hreben, M and Bolton-King, RS ORCID: https://orcid.org/0000-0002-9208-7857, 2025. Novel imaging solution to quantify, evaluate and compare gunshot residue patterns. Forensic Science International. ISSN 0379-0738

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Abstract

The analysis of gunshot residue (GSR) patterns is crucial for the reconstruction of shooting incidents. Established chemographic methods, such as the Modified Griess and Sodium Rhodizonate tests, are effective but also destructive, hazardous and not readily quantifiable. This paper presents proof-of-principle for a new quantifiable method to compare GSR patterns and evaluate the performance of a flatbed scanner, modified by the manufacturer to operate in blue-green fluorescence (BGF, 450 nm excitation/630 nm barrier) and infrared reflectance (IR) modes (850 nm). The effects of 9 mm Luger ammunition brand as well as fabric color and type were evaluated using the spectroscopic scanner and Weber contrast method developed. The unenhanced Weber contrast among ammunition brands ranged from 0.28 to 0.85 when viewed upon a single cotton fabric background. Darkening caused by smoke deposits appeared to dampen propellant-particle brightness, at least for certain brands of ammunition, but did not fully explain the difference in contrast between brands. Analysis of 248 representative fabric swatches revealed that suitable contrast could be achieved after enhancement for 92% (BGF mode) and 91% (IR mode) of those evaluated, with median Weber contrast values of 10.3 (BGF) and 4.83 (IR) achieved following enhancement. These were well above the Weber threshold required for human visual perception (~0.1) and demonstrate its potential use as a comparison tool in forensic practice and research. Evaluation of muzzle-to-target distance estimation using this scanner will be the subject of a future study.

Item Type:	Journal article
Publication Title:	Forensic Science International
Creators:	Kusluski, M.A., Hreben, M. and Bolton-King, R.S.
Publisher:	Elsevier BV
Date:	12 November 2025
ISSN:	0379-0738
Identifiers:	Number Type 10.1016/j.forsciint.2025.112721 DOI 2530853 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Borcherds
Date Added:	19 Nov 2025 11:41
Last Modified:	19 Nov 2025 11:41
URI:	https://irep.ntu.ac.uk/id/eprint/54776

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