Abstract
This work proposes a method of analysis of geometric features generated from hand-written text to verify a supposition that a given sample of text of unclear authorship (e.g., a signature or initials) and some given reference text of known authorship have been written by the same author. The method is targeted to problems where the reference material is relatively large and the sample of unclear authorship is small, hence the number of feature vectors for the two groups compared is highly unbalanced. This makes the problem computationally challenging as standard approaches based on statistical hypothesis testing to compare distributions cannot be used. We propose a method to estimate the likelihood that the set of features observed in the small sample comes from the distribution generated from the reference material. This approach can be used to help discover or prove a forgery in documents.
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Maciejewski, H., Ptak, R. (2011). Analysis of Geometric Features of Handwriting to Discover a Forgery. In: Zamojski, W., Kacprzyk, J., Mazurkiewicz, J., Sugier, J., Walkowiak, T. (eds) Dependable Computer Systems. Advances in Intelligent and Soft Computing, vol 97. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21393-9_11
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DOI: https://doi.org/10.1007/978-3-642-21393-9_11
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