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

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

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

File

2023-Crawford-StatisticalApproach.pdf (6.87 MB)

Date

2023-09

Authors

Crawford, Amy M.

Ommen, Danica M.

Carriquiry, Alicia

Publisher

Wiley Periodicals LLC on behalf of American Academy of Forensic Sciences

Abstract

We 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.

Academic or Administrative Unit

Statistics

Center for Statistics and Applications in Forensic Evidence

Type

Article

Comments

This article is published as Crawford AM, Ommen DM, Carriquiry AL. A statistical approach to aid examiners in the forensic analysis of handwriting. J Forensic Sci. 2023;68:1768–79. https://doi.org/10.1111/1556-4029.15337. © 2023 The Authors. Posted with permission of CSAFE.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.