Amy M. Crawford, Danica M. Ommen, Alicia L. Carriquiry

A statistical approach to aid examiners in the forensic analysis of handwriting

  • Genetics
  • Pathology and Forensic Medicine
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AbstractWe develop a statistical approach to model handwriting that accommodates all styles of writing (cursive, print, connected print). The goal is to compute a posterior probability of writership of a questioned document given a closed set of candidate writers. Such probabilistic statements can support examiner conclusions and enable a quantitative forensic evaluation of handwritten documents. Writing is treated as a sequence of disjoint graphical structures, which are extracted using an automated and open‐source process. The graphs are grouped based on the similarity of their shapes through a K‐means clustering template. A person's writing pattern can be characterized by the rate at which graphs are emitted to each cluster. The cluster memberships serve as data for a Bayesian hierarchical model with a mixture component. The rate of mixing between two parameters in the hierarchy indicates writing style.

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