Objective Analysis of Impressed Chisel Toolmarks

Historical and recent challenges to the practice of comparative forensic examination have created a driving force for the formation of objective methods for toolmark identification. In this study , fifty sequentially manufactured chisels were used to create impression toolmarks in lead (500 toolmarks total). An algorithm previously used to statistically separate known matching and nonmatching striated screwdriver marks and quasi-striated plier marks was used to evaluate the chisel marks. Impression toolmarks, a more complex form of toolmark, pose a more difficult test for the algorithm that was originally designed for striated toolmarks. Results show in this instance that the algorithm can separate matching and nonmatching impression marks, providing further validation of the assumption that toolmarks are identifiably unique.     

Analysis of explosive damage in metals using orientation imaging microscopy

The goal of this project was to determine whether quantitative information concerning the size and nature of an explosive blast could be determined using Orientation Imaging Microscopy (OIM) to analyze the texture of blast-affected metal. Selected 1018 steel and 2024 aluminum samples were subjected to various explosive blasts chosen to simulate a wide range of possible pressure waves. The explosives used were PBX 9404, Comp-C4, Gelmax, and Bullseye. The explosive tests were carried out at Sandia National Laboratory, and the OIM analysis was conducted at Ames Laboratory. It was discovered that while suitable patterns could be obtained from the steel samples, the oxide layer present on the surface of the aluminum samples prevented these samples from being studied. The results of the OIM studies on the steel samples indicate that damage can be tracked using OIM imaging and that Comp-C4 seems to produce patterns significantly different than the other explosives.     

Angular Determination of Toolmarks Using a Computer‐Generated Virtual Tool

A blind study to determine whether virtual toolmarks created using a computer could be used to identify and characterize angle of incidence of physical toolmarks was conducted. Six sequentially manufactured screwdriver tips and one random screwdriver were used to create toolmarks at various angles. An apparatus controlled tool angle. Resultant toolmarks were randomly coded and sent to the researchers, who scanned both tips and toolmarks using an optical profilometer to obtain 3D topography data. Developed software was used to create virtual marks based on the tool topography data. Virtual marks generated at angles from 30 to 85° (5° increments) were compared to physical toolmarks using a statistical algorithm. Twenty of twenty toolmarks were correctly identified by the algorithm. On average, the algorithm misidentified the correct angle of incidence by ?6.12°. This study presents the results, their significance, and offers reasons for the average angular misidentification.     

Virtual Tool Mark Generation for Efficient Striation Analysis,

This study introduces a tool mark analysis approach based upon 3D scans of screwdriver tip and marked plate surfaces at the micrometer scale from an optical microscope. An open‐source 3D graphics software package is utilized to simulate the marking process as the projection of the tip's geometry in the direction of tool travel. The edge of this projection becomes a virtual tool mark that is compared to cross‐sections of the marked plate geometry using the statistical likelihood algorithm introduced by Chumbley et al. In a study with both sides of six screwdriver tips and 34 corresponding marks, the method distinguished known matches from known nonmatches with zero false‐positive matches and two false‐negative matches. For matches, it could predict the correct marking angle within ±5–10°. Individual comparisons could be made in seconds on a desktop computer, suggesting that the method could save time for examiners.     

Development of a Mobile Toolmark Characterization/Comparison System

Since the development of the striagraph, various attempts have been made to enhance forensic investigation through the use of measuring and imaging equipment. This study describes the development of a prototype system employing an easy‐to‐use software interface designed to provide forensic examiners with the ability to measure topography of a toolmarked surface and then conduct various comparisons using a statistical algorithm. Acquisition of the data is carried out using a portable 3D optical profilometer, and comparison of the resulting data files is made using software named “MANTIS” (Mark and Tool Inspection Suite). The system has been tested on laboratory‐produced markings that include fully striated marks (e.g., screwdriver markings), quasistriated markings produced by shear‐cut pliers, impression marks left by chisels, rifling marks on bullets, and cut marks produced by knives. Using the system, an examiner has the potential to (i) visually compare two toolmarked surfaces in a manner similar to a comparison microscope and (ii) use the quantitative information embedded within the acquired data to obtain an objective statistical comparison of the data files. This study shows that, based on the results from laboratory samples, the system has great potential for aiding examiners in conducting comparisons of toolmarks.     

Optimization of a Statistical Algorithm for Objective Comparison of Toolmarks

Due to historical legal challenges, there is a driving force for the development of objective methods of forensic toolmark identification. This study utilizes an algorithm to separate matching and nonmatching shear cut toolmarks created using fifty sequentially manufactured pliers. Unlike previously analyzed striated screwdriver marks, shear cut marks contain discontinuous groups of striations, posing a more difficult test of algorithm applicability. The algorithm compares correlation between optical 3D toolmark topography data, producing a Wilcoxon rank sum test statistic. Relative magnitude of this metric separates the matching and nonmatching toolmarks. Results show a high degree of statistical separation between matching and nonmatching distributions. Further separation is achieved with optimized input parameters and implementation of a “leash” preventing a previous source of outliers—however complete statistical separation was not achieved. This paper represents further development of objective methods of toolmark identification and further validation of the assumption that toolmarks are identifiably unique.     

Validation of Tool Mark Comparisons Obtained Using a Quantitative,Comparative, Statistical Algorithm

Abstract: A statistical analysis and computational algorithm for comparing pairs of tool marks via profilometry data is described. Empirical validation of the method is established through experiments based on tool marks made at selected fixed angles from 50 sequentially manufactured screwdriver tips. Results obtained from three different comparison scenarios are presented and are in agreement with experiential knowledge possessed by practicing examiners. Further comparisons between scores produced by the algorithm and visual assessments of the same tool mark pairs by professional tool mark examiners in a blind study in general show good agreement between the algorithm and human experts. In specific instances where the algorithm had difficulty in assessing a particular comparison pair, results obtained during the collaborative study with professional examiners suggest ways in which algorithm performance may be improved. It is concluded that the addition of contextual information when inputting data into the algorithm should result in better performance.