Quantitative comparison of striated toolmarks

•Automated registration (alignment) and comparison of striated screwdriver toolmarks.•High discrimination between KMs and KNMs for large differences in angle of attack.•Separation of relevant and non-relevant (e.g. sub-class) geometric structures.•Comparison of the method with the performance of toolmark examiners.•Comparison of results using 2D and 3D data and using different screwdriver types.

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.