Forensic surface metrology: tool mark evidence

Abstract

Over the last several decades, forensic examiners of impression evidence have come under scrutiny in the courtroom due to analysis methods that rely heavily on subjective morphological comparisons. Currently, there is no universally accepted system that generates numerical data to independently corroborate visual comparisons. Our research attempts to develop such a system for tool mark evidence, proposing a methodology that objectively evaluates the association of striated tool marks with the tools that generated them. In our study, 58 primer shear marks on 9 mm cartridge cases, fired from four Glock model 19 pistols, were collected using high-resolution white light confocal microscopy. The resulting three-dimensional surface topographies were filtered to extract all "waviness surfaces"-the essential "line" information that firearm and tool mark examiners view under a microscope. Extracted waviness profiles were processed with principal component analysis (PCA) for dimension reduction. Support vector machines (SVM) were used to make the profile-gun associations, and conformal prediction theory (CPT) for establishing confidence levels. At the 95% confidence level, CPT coupled with PCA-SVM yielded an empirical error rate of 3.5%. Complementary, bootstrap-based computations for estimated error rates were 0%, indicating that the error rate for the algorithmic procedure is likely to remain low on larger data sets. Finally, suggestions are made for practical courtroom application of CPT for assigning levels of confidence to SVM identifications of tool marks recorded with confocal microscopy.

Applying 3D measurements and computer matching algorithms to two firearm examination proficiency tests

“…Many other metrics for quantifying pattern similarity for firearms evidence exists [4–7]. At the National Institute of Standards and Technology (NIST) a method called Congruent Matching Cells (CMC) has been developed [3].…”

“…The approaches to addressing the issues raised by the report [2] generally fall into two categories. The first is to develop measurement systems and computer algorithms that are able to quantify the degree of similarity between tool marks [3–7]. Using these systems and an appropriately selected, representative database of firearms evidence, it is possible to estimate error rates for comparisons and obtain consistent, objective similarity scores.…”

Automatic Comparison and Evaluation of Impressions Left by a Firearm on Fired Cartridge Cases

“…These research efforts have shown that topography measurements in 3D allow good accuracy, while at the same time, maintaining a high level of reproducibility. The main objectives of the statistical analysis carried out in these previous studies were either to measure the global discrimination power of the 3D system, establishing the respective error rates (often used to assess the discrimination power of the analyzed impressions) , or to measure the efficiency of these systems when they are used in the context of a database search . The objective of the present study is different as it aims to obtain an objective assignment of the weight of the evidence derived from a set of observations between two entities measured in 3D.…”

Conference Proceedings: 2015 Impression, Pattern, and Trace Evidence Symposium

“…As a "frequentist"-based approach to association quality, conformal prediction theory is used to assign orthodox confidence levels to each toolmark identification. This is accomplished via Vovk, Gammerman, and Shafer's (2005) formula for a nonconformity measure using the SVM Lagrange multipliers (Gambino et al, 2011;Petraco et al, 2012). As a test of the method's validity, on-line prediction plots are constructed for successive toolmark identifications.…”