Abstract
The presented work focuses on the method of handwritten signature recognition, which takes into consideration a lack of repetition of the signature features. Up till now signature recognition methods based only on signature features selection. Proposed approach allows to determine both the most useful features and methods which these features should be analyzed. In the developed method different features and similarity measures can be freely selected. Additionally, selected features and similarity measures can be different for every person.
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Doroz, R., Porwik, P. (2011). Handwritten Signature Recognition with Adaptive Selection of Behavioral Features. In: Chaki, N., Cortesi, A. (eds) Computer Information Systems – Analysis and Technologies. Communications in Computer and Information Science, vol 245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27245-5_17
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DOI: https://doi.org/10.1007/978-3-642-27245-5_17
Publisher Name: Springer, Berlin, Heidelberg
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