Quantitative matching of forensic evidence fragments utilizing 3D microscopy analysis of fracture surface replicas

• NCJ Number: 304494
• Journal: Journal of Forensic Sciences Dated: March 2022
• Author(s): Bishoy Dawood; Carlos Llosa-Vite; Geoffrey Z. Thompson; Barbara K. Lograsso; Lauren K. Claytor; John Vanderkolk; William Meeker; Ranjan Maitra; Ashraf Bastawros
• Date Published: March 2022
• Grant Number(s): 2015-DN-BX-K056; 2018-R2-CX-0034
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)
• Award: Quantitative Tools for Examination of Microscopic Fracture Surface Topology and Degradation for Physical Match Analysis of Evidence; Physics and Statistical Models for Physical Match Analysis Utilizing 3D Microscopy of Fracture Surfaces

Annotation

Since silicone casts are widely used by practitioners in the comparative analysis of forensic items and fractured surfaces carry unique details that can provide accurate quantitative comparisons of forensic fragments, the current study applied a statistical analysis comparison protocol to a set of 3D topological images of fractured surface pairs and their replicas to provide confidence in the quantitative statistical comparison between fractured items and their silicone cast replicas.

Abstract

A set of 10 fractured stainless steel samples were fractured from the same metal rod under controlled conditions and were replicated using a standard forensic casting technique. Six 3D topological maps with 50% overlap were acquired for each fractured pair. Spectral analyses were utilized to identify the correlation between topological surface features at different length scales of the surface topology. We selected two frequency bands over the critical wavelength (greater than two-grain diameters) for statistical comparison. The statistical model utilized a matrix-variate t-distribution that accounts for overlap between images to model match and non-match population densities. A decision rule identified the probability of matched and unmatched pairs of surfaces. The proposed methodology correctly classified the fractured steel surfaces and their replicas with a posterior probability of match exceeding 99.96%. Moreover, the replication technique shows potential in accurately replicating fracture surface topological details with a wavelength greater than 20 μm, which far exceeds the feature comparison range on most metallic alloy surfaces. The framework establishes the basis and limits for forensic comparison of fractured articles and their replicas while providing a reliable fracture mechanics-based quantitative statistical forensic comparison. (Publisher Abstract)