Influence of the axial rotation angle on tool mark striations.

A tool's axial rotation influences the geometric properties of a tool mark. The larger the axial rotation angle, the larger the compression of structural details like striations. This complicates comparing tool marks at different axial rotations. Using chisels, tool marks were made from 0° to 75° axial rotation and compared using an automated approach Baiker et al. [10]. In addition, a 3D topographic surface of a chisel was obtained to generate virtual tool marks and to test whether the axial rotation angle of a mark could be predicted. After examination of the tool mark and chisel data-sets it was observed that marks lose information with increasing rotation due to the change in relative distance between geometrical details on the tool and the disappearance of smaller details. The similarity and repeatability were high for comparisons between marks with no difference in axial rotation, but decreasing with increased rotation angle from 0° to 75°. With an increasing difference in the rotation angles, the tool marks had to be corrected to account for the different compression factors between them. For compression up to 7.5%, this was obtained automatically by the tool mark alignment method. For larger compression, manually re-sizing the marks to the uncompressed widths at 0° rotation before the alignment was found suitable for successfully comparing even large differences in axial rotation. The similarity and repeatability were decreasing however, with increasing degree of re-sizing. The quality was assessed by determining the similarity at different detail levels within a tool mark. With an axial rotation up to 75°, tool marks were found to reliably represent structural details down to 100µm. The similarity of structural details below 100µm was dependent on the angle, with the highest similarity at small rotation angles and the lowest similarity at large rotation angles. Filtering to remove the details below 100µm lead to consistently higher similarity between tool marks at all angles and allowed for a comparison of marks up to 75° axial rotation. Finally, generated virtual tool mark profiles with an axial rotation were compared to experimental tool marks. The similarity between virtual and experimental tool marks remained high up to 60° rotation after which it decreased due to the loss in quality in both marks. Predicting the rotation angle is possible under certain conditions up to 45° rotation with an accuracy of 2.667±0.577° rotation.

Virtual and simulated striated toolmarks for forensic applications.

Large numbers of experimental toolmarks of screwdrivers are often required in casework of toolmark examiners and in research environments alike, to be able to recover the angle of attack of a crime scene mark and to determine statistically meaningful properties of toolmarks respectively. However, in practice the number of marks is limited by the time needed to create them. In this article, we present an approach to predict how a striated mark of a particular tool would look like, using 3D surface datasets of screwdrivers. We compare these virtual toolmarks qualitatively and quantitatively with real experimental marks in wax and show that they are very similar. In addition we study toolmark similarity, dependent on the angle of attack, with a very high angular resolution of 1°. The results show that for the tested type of screwdriver, our toolmark comparison framework yields known match similarity scores that are above the mean known non-match similarity scores, even for known match differences in angle of attack of up to 40°. In addition we demonstrate an approach to automatically recover the angle of attack of an experimental toolmark and experiments yield high accuracy and precision of 0.618 ± 4.179°. Furthermore, we present a strategy to study the structural elements of striated toolmarks using wavelet analysis, and show how to use the results to simulate realistic toolmarks.

Toolmark variability and quality depending on the fundamental parameters: Angle of attack, toolmark depth and substrate material.

The traditional way of visual toolmark comparison includes subjective judgments. Automated methods using computers are a possibility to render a comparison more objective, but they require the statistical properties, like the similarity and variability, of toolmarks to be determined quantitatively. Several parameters, that play a role during toolmark creation, are statistically analyzed in this article. We determined the same toolmark and the different toolmark similarity as well as variability of known matching toolmarks created in wax and compared the results with the similarity and variability of known non-matching toolmarks. In addition we studied the influence of the substrate materials wax and lead and the angle of attack on toolmark similarity and variability. Furthermore, we present an approach to determine toolmark quality, defined as how well structural details are preserved in the toolmark, to assist toolmark examiners in deciding, which structural details are reliable in a mark. We studied the influence of the substrate material, the angle of attack and the depth of a toolmark on the quality. The results show that for known matching toolmarks, the variability is very low within a toolmark and between toolmarks in wax, given that the parameters angle of attack and depth are held constant. Geometrical details are reliably represented down to 10-50µm and toolmark similarity is clearly higher than known non-matching similarities. The comparison of wax and lead shows that wax is a good alternative as a substrate material for experimental toolmarks, capable of reliably representing structural details down to 10-25µm. For finer details, lead is a better choice but might alter the original state of a tool. With increasing angle of attack, toolmark variability increases and toolmark quality decreases. Therefore it is advantageous to push the tool instead of pulling during toolmark creation for angles of attack above ≈45°. The quality also decreases with increasing toolmark depth, but only up to ≈300µm. Therefore toolmarks should be created as shallow as possible in the substrate material.

Quantitative comparison of striated toolmarks.

A comparison of striated toolmarks by human examiners is dependent on the experience of the expert and includes a subjective judgment within the process. In this article an automated method is presented for objective comparison of striated marks of screwdrivers. The combination of multi-scale registration (alignment) of toolmarks, that accounts for shift and scaling, with global cross correlation as objective toolmark similarity metric renders the approach robust with respect to large differences in angle of attack and moderate toolmark compression. In addition, a strategy to distinguish between relevant and non-relevant spatial frequency ranges (geometric details) is presented. The performance of the method is evaluated using 3D topography scans of experimental toolmarks of 50 unused screwdrivers. Known match and known non-match similarity distributions are estimated including a large range of angles of attack (15, 30, 45, 60 and 75°) for the known matches. It is demonstrated that the system has high discriminatory power, even if the toolmarks are made at a difference in angle of attack of larger than 15°. The probability distributions are subsequently employed to determine likelihood ratios. A comparison of the results of the automated method with the outcome of a toolmark comparison experiment involving three experienced toolmark examiners reveals, that the automated system is more powerful in correctly supporting the hypothesis of common origin for toolmarks with a large difference in angle of attack (30°). In return, the rate of toolmark comparisons that yield incorrect support for the hypothesis of common origin is higher for the automated system. In addition, a comparison between estimating known match and known non-match distributions using 2D and 3D data is presented and it is shown that for toolmarks of unused screwdrivers, relying on 3D is slightly better than relying on 2D data. Finally, a comparison between estimating known match and known non-match distributions for two different types of screwdrivers suggests, that the method may be used for comparing marks of other tools as well.