We consider the problem setting in which we have two sets of texts in digital form and would like to quantify our beliefs that the two sets of texts were
When a crime is committed, law enforcement directs crime scene experts to obtain evidence that may be pertinent to identifying the perpetrator(s). Much of this evidence comes in the form
Forensic questioned document examiners still largely rely on visual assessments and expert judgment to determine the provenance of a handwritten document. Here, we propose a novel approach to objectively compare
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
Identifying the source of handwriting is an important application in the field of forensic science that addresses questioned document evidence found in criminal cases and civil litigation. It is difficult,
Questioned Document Examiners (QDEs) are tasked with analyzing handwriting evidence to make source (or writership) determinations. The Center for Statistics and Applications of Forensic Evidence (CSAFE) has previously developed computational
Handwriting comparative analysis is based on the principle that no two individuals can produce the same writing and that an individual cannot exactly reproduce his/her handwriting. This project aims to