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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.
Chumbley et al. (Mon,) studied this question.