A statistical approach to aid examiners in the forensic analysis of handwriting
Date
2023-09
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Wiley Periodicals LLC on behalf of American Academy of Forensic Sciences
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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.
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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.
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.