Forensic toolmark comparisons are currently performed subjectively by humans, which leads to a lack of consistency and accuracy. There is little evidence that examiners can determine whether pairs of marks were made by the same tool or different tools. There is also little evidence that they can make this classification when marks are made under different conditions, such as different angles of attack or direction of mark generation. We generate original toolmark data in 3D, extract the signal from each toolmarks, and train an algorithm to compare toolmark signals objectively. We find that toolmark signals cluster by tool, and not by angle or direction. That is, the variability within tool, regardless of angle/direction, is smaller than the variability between tools. The known-match and known-non-match densities of the similarities of pairs of marks have a small overlap, even when accounting for dependencies in the data, making them a useful instrument for determining whether a new pair of marks was made by the same tool. We provide a likelihood ratio approach as a formal method for comparing toolmark signals with a measure of uncertainty. This empirically trained, open-source method can be used by forensic examiners to compare toolmarks objectively and thus improve the reliability of toolmark comparisons. This can, in turn, reduce miscarriages of justice in the criminal justice system.

鉴定工具痕迹比对是一项目前由人类主观完成的工作，导致缺乏一致性和准确性。我们通过生成3D原始工具痕迹数据、提取信号并训练算法来客观比较工具痕迹，发现工具痕迹信号按工具聚类，而非角度或方向。我们提供一种基于似然比的方法来比较工具痕迹信号，帮助法医鉴定人员客观比对工具痕迹，从而提高比对可靠性，减少刑事司法系统中的冤假错案。

改变法医工具痕迹分析：一种客观透明的比对算法