Project LS-2005-WI-A

Titel Forensic writer identification: Machines versus Humans

Forensic writer identification enjoys renewed interest since 9/11 and the "antrax letters". The goal is to find the identity of an unknown writer of a questioned document (e.g., threat letter), given a database of handwritten samples by known suspects. Interestingly, this application has resisted the use of artificial intelligence, pattern-recognition and image-processing technology. Human experts claim that they can do this job much more accurately. However, technology has advanced considerably by recent work in Groningen (Schomaker/Bulacu). In this project, collected data will be analyzed, using the Beowulf cluster of >100 computers, in order to find optimal parameters and features for realistic forensic handwritten samples.

The ability to program (Java, C, C++) is a prerequisite. Affinity with statistical analysis is useful.

Supervisor: Lambert Schomaker

A questioned sample (top, orange border) and a hit list of the forensic writer search engine. The first nearest neigbour is in this case fortunately the correct writer (image border marked orange).