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A Signature Complexity Measure to Select Reference Signatures for Online Signature Verification

Authors: Christian Kahindo; Sonia Garcia-Salicetti; Nesma Houmani;

A Signature Complexity Measure to Select Reference Signatures for Online Signature Verification

Abstract

This paper presents an original procedure for selecting the reference online signature instances of a writer, an important issue for any effective signature verifier. To this end, for each signature instance, we propose a novel complexity measure, by exploiting a global description of signatures in the frequency domain as well as a global statistical modelling of each signature instance. To select the reference signatures, we propose a method based on the distribution of complexity values for all the available genuine signatures. The 2500 genuine samples of MCYT-100 online database are used in this study. Experimental results show the effectiveness of the method and of the here proposed complexity measure for this specific task.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Average
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