Estimating the probability of accidental mark locations on a shoe sole
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Footwear comparison is an important type of forensic evidence used to link between a suspect's shoe and a footprint found at a crime scene. Besides the type and the size of the shoe, investigators compare the trace to the source using randomly acquired characteristics (RACs), such as scratches or holes, in order to distinguish between similar shoes. However, to date, the distribution of RAC characteristics has not been investigated thoroughly, and the evidential value of RACs is yet to be explored. A first important question concerns the distribution of the location of RACs on shoe soles in the general population, which can serve as a benchmark for comparison. In this paper, the location of RACs is modeled as a point process over the shoe sole and a data set of independent shoes is used to estimate its rate function. As the shoes are differentiated by shape, level of wear and tear and contact surface, this process is complicated. This paper presents methods that take into account these challenges, either by using natural cubic splines on high resolution data, or by using a piecewise-constant model on larger regions defined by forensic experts. It is shown that RACs are likely to appear at certain locations, corresponding to the foot morphology. The results can guide investigators in determining the evidential value of footprint comparison.
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