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The first consistent and reproducible evaluation of the effect of aging on dynamic signature is reported. Experiments are carried out on a database generated from two previous datasets which were acquired, under very similar conditions, in 6 sessions distributed in a 15 month time span. Three different systems, representing the current most popular approaches in signature recognition, are used in the experiments, proving the degradation suffered by this trait with the passing of time. Several template update strategies are also studied as possible measures to reduce the impact of aging on the system's performance. Different results regarding the way in which signatures tend to change with time, and their most and least stable features, are also given.
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