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Webinar: handwriter: A Demonstration and Update on CSAFE Handwriting Analysis
Tuesday, October 18, 2022 at 11:00 am - 12:00 pm CDTFree
CSAFE invites researchers, collaborators, and members of the broader forensics and statistics communities to participate in our Summer 2022 Webinar Series on Tuesday, October 18, 2022, from 11:00am-Noon CT. The presentation will be “handwriter: A Demonstration and Update on CSAFE Handwriting Analysis.”
Director, Center for Statistics and Applications in Forensic Evidence (CSAFE)
Distinguished Professor and President’s Chair, Department of Statistics – Iowa State University
Forensic handwriting analysis relies on the principle of individuality: no two writers produce identical writing, and given enough quality and quantity of writing, it is possible to infer whether two documents were written by the same person. Forensic handwriting analysis is carried out by examiners trained to find subtle differences and similarities between a questioned document and a reference sample. Examiners visually compare samples and offer an opinion regarding the source of the questioned document.
In the last 10-15 years, researchers have proposed algorithmic tools to complement examiners’ visual assessments. A well-known software system called FLASH ID (Sciometrics, LLC) first decomposes the image of a questioned sample into structures called graphemes and then characterizes them by their topology and shape. Given a closed set of reference samples, the software computes a score that quantifies the similarity between the questioned document and the references. FLASH ID has been extensively tested and has been shown to exhibit very good accuracy.
At CSAFE, we are working on semi-automated methods suitable for closed or for open sets of reference writers, and for the examination of samples at the level of words or at the level of graphical structures similar, but not identical to graphemes. In the webinar we will describe each of the different methods, and show initial but promising results. When the reference set of writers is closed we use a Bayesian approach that outputs a probability of writership for each writer in the set. Because the output is an estimated probability, the interpretation of results is straightforward. We are still developing and testing the word-based approach and the more algorithmic approach that can be used when the set of potential writers is open, but can show some initial results and our plans for future developments. We will demonstrate our software to implement these methods: handwriter. The program is not yet fully functional, but an early version is in the public domain and can be freely accessed at https://github.com/CSAFE-ISU/handwriter.
Webinars are free and open to the public, but researchers, collaborators and members of the broader forensics and statistics communities are encouraged to attend. Space is only guaranteed for the first 150 people registered. Each 60-minute webinar will allow for discussion and questions.
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