Location distribution of randomly acquired characteristics on a shoe sole

Naomi Kaplan-Damary*, Micha Mandel, Yoram Yekutieli, Yaron Shor, Sarena Wiesner

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Footwear comparison is used to link between a suspect's shoe and a shoeprint found at a crime scene. Forensic examiners compare the two items, and the conclusion reached is based on class characteristics and randomly acquired characteristics (RACs), such as scratches or holes. An important question concerns the distribution of the location of RACs on shoe soles, which can serve as a benchmark for comparison. This study examines the probability of observing RACs in different areas of a shoe sole using a database of approximately 13,000 RACs observed on 386 outsoles. The analysis is somewhat complicated as the shoes are differentiated by shape and contact surface, and the RACs' locations are subject to measurement errors. A method that takes into account these challenges is presented. All impressions are normalized to a standardized axis to allow for inter-comparison of RACs on outsoles of different sizes and contact areas, and RACs are localized to one of 14 subareas of the shoe sole. Expected frequencies in each region are assumed to be Poisson distributed with rate parameters that depend on the subarea and the contact surface. Three different estimation approaches are studied: a naive crude approach, a shoe-specific random effects model, and an estimate that is based on conditional maximum likelihood. It is shown that the rate is not uniform across the shoe sole and that RACs are approximately twice as likely to appear at certain locations, corresponding to the foot's morphology. The results can guide investigators in determining a shoeprint's evidential value.

Original languageAmerican English
Pages (from-to)1801-1809
Number of pages9
JournalJournal of Forensic Sciences
Volume67
Issue number5
DOIs
StatePublished - Sep 2022

Bibliographical note

Publisher Copyright:
© 2022 The Authors. Journal of Forensic Sciences published by Wiley Periodicals LLC on behalf of American Academy of Forensic Sciences.

Keywords

  • accidental marks
  • conditional maximum likelihood
  • footwear impression
  • random effects model
  • randomly acquired characteristics
  • shoeprints

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