Allograph based writer identification, handwriting analysis and character recognition
In case you object to the disclosure of your thesis, you can contact email@example.com
[S.l. : s.n.]
Number of pages
Radboud Universiteit Nijmegen, 4 oktober 2010
Promotores : Schomaker, L.R.B., Desain, P.W.M. Co-promotor : Vuurpijl, L.G.
Display more detailsDisplay less details
SW OZ DCC KI
SW OZ NICI KI
SubjectCognitive artificial intelligence; DI-BCB_DCC_Theme 4: Brain Networks and Neuronal Communication
In this thesis, techniques and features are described that were developed for the automatic comparison of handwritten characters by first matching them to prototypical character shapes (allographs). These techniques and features were evaluated in experiments simulating different real-world applications. The majority of the experiments regard forensic writer identification, where the objective is to find the writer of a piece of handwriting by comparing it to a large set of handwritten documents of which the writer is already known. The assumption is that if two documents contain many similar allographs, they may have been produced by the same writer. In the experiment described, it is demonstrated that using the techniques and features, it is indeed possible to match the correct writer with a piece of unknown handwriting. Other experiments were performed to evaluate the usefulness of the techniques and features for the classification of hand-drawn symbols and characters in differentive is not to find out who produced the writing, but what it represents) and the analysis of children's handwriting to diagnose Developmental Coordination Disorder.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.