Individuality of alphabet knowledge in online writer identification |
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Authors: | Guo Xian Tan Christian Viard-Gaudin Alex C Kot |
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Affiliation: | 1. Centre for Information Security, Nanyang Technological University, Singapore, Singapore 2. IRCCyN - UMR CNRS 6597, Ecole Polytechnique de l’Université de Nantes, Nantes Cedex 3, France
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Abstract: | Allograph prototype approaches for writer identification have been gaining popularity recently due to its simplicity and promising
identification rates. Character prototypes that are used as allographs produce a consistent set of templates that models the
handwriting styles of writers, thereby allowing high accuracies to be attained. We hypothesize that the alphabet knowledge
inherent in such character prototypes can provide additional writer information pertaining to their styles of writing and
their identities. This paper utilizes a character prototype approach to establish evidence that knowledge of the alphabet
offers additional clues which help in the writer identification process. This paper then introduces an alphabet information
coefficient (AIC) to better exploit such alphabet knowledge for writer identification. Our experiments showed an increase
in writer identification accuracy from 66.0 to 87.0% on a database of 200 reference writers when alphabet knowledge was used.
Experiments related to the reduction in dimensionality of the writer identification system are also reported. Our results
show that the discriminative power of the alphabet can be used to reduce the complexity while maintaining the same level of
performance for the writer identification system. |
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