Skip to content

Handwriting Identification using Random Forests and Score-based Likelihood Ratios

Journal: Statistical Analysis and Data Mining
Published: 2021
Primary Author: Madeline Johnson
Secondary Authors: Danica Ommen

Handwriting analysis is conducted by forensic document examiners who are able to visually recognize characteristics of writing to evaluate the evidence of writership. Recently, there have been incentives to investigate how to quantify the similarity between two written documents to support the conclusions drawn by experts. We use an automatic algorithm within the ‘handwriter’ package in R, to decompose a hand- written sample into small graphical units of writing. These graphs are sorted into 40 exemplar groups or clusters. We hypothesize that the frequency with which a per- son contributes graphs to each cluster is characteristic of their handwriting. Given two questioned handwritten documents, we can then use the vectors of cluster frequencies to quantify the similarity between the two documents. We extract features from the difference between the vectors and combine them using a random forest. The output from the random forest is used as the similarity score to compare documents. We estimate the distributions of the similarity scores computed from multiple pairs of documents known to have been written by the same and by different persons, and use these estimated densities to obtain score-based likelihood ratios (SLRs) that rely on different assumptions. We find that the SLRs are able to indicate whether the similarity observed between two documents is more or less likely depending on writership.

Related Resources

Tutorial on Likelihood Ratios with Applications in Digital Forensics

Tutorial on Likelihood Ratios with Applications in Digital Forensics

This CSAFE webinar was held on September 15, 2022. Presenters: Rachel Longjohn PhD Student – Department of Statistics, University of California, Irvine Dr. Padhraic Smyth Chancellor’s Professor – Departments of…
Ensemble SLRs for Forensic Evidence Comparison

Ensemble SLRs for Forensic Evidence Comparison

This CSAFE webinar was held on August 25, 2022. Presenter: Danica Ommen Assistant Professor – Department of Statistics, Iowa State University Presentation Description: To strengthen the statistical foundations of forensic…
Likelihood Ratios for Categorical Evidence With Applications in Digital Evidence

Likelihood Ratios for Categorical Evidence With Applications in Digital Evidence

The following poster was presented at the 74th Annual Scientific Conference of the American Academy of Forensic Sciences (AAFS), Seattle, Washington, February 21-25, 2022.
Statistical support for weight of evidence determinations of handwriting evidence

Statistical support for weight of evidence determinations of handwriting evidence

Handwriting analysis is conducted through the expertise of Forensic Document Examiners (FDEs) by visually comparing writing samples. Through their training and years of experience, FDEs are able to recognize critical…