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<identifier>oai:HAL:hal-01165871v1</identifier>
<datestamp>2015-06-22</datestamp>
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<setSpec>collection:IGS2015</setSpec>
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<metadata><dc>
<publisher>HAL CCSD</publisher>
<title lang=en>A Dissimilarity Measure for On-Line Signature Verification Based on the Sigma-Lognormal Model</title>
<creator>Fischer, Andreas</creator>
<creator>Plamondon, Réjean</creator>
<contributor>Laboratoire scribens ; Ecole Polytechnique de Montréal (EPM)</contributor>
<contributor>iCoSys Institute ; University of Applied Sciences and Arts Northwestern Switzerland (HES-SO)</contributor>
<contributor>DIUF Department ; Department of Biology, University of Fribourg, Switzerland</contributor>
<description>International audience</description>
<source>17th Biennial Conference of the International Graphonomics Society</source>
<coverage>Pointe-à-Pitre, Guadeloupe</coverage>
<contributor>International Graphonomics Society (IGS)</contributor>
<contributor>Université des Antilles (UA)</contributor>
<contributor>Céline Rémi</contributor>
<contributor>Lionel Prévost</contributor>
<contributor>Eric Anquetil</contributor>
<identifier>hal-01165871</identifier>
<identifier>https://hal.univ-antilles.fr/hal-01165871</identifier>
<identifier>https://hal.univ-antilles.fr/hal-01165871/document</identifier>
<identifier>https://hal.univ-antilles.fr/hal-01165871/file/IGS_2015_submission_11.pdf</identifier>
<source>https://hal.univ-antilles.fr/hal-01165871</source>
<source>Céline Rémi; Lionel Prévost; Eric Anquetil. 17th Biennial Conference of the International Graphonomics Society, Jun 2015, Pointe-à-Pitre, Guadeloupe. 2015, Drawing, Handwriting Processing Analysis: New Advances and Challenges</source>
<language>en</language>
<subject lang=en>on-line signature verification</subject>
<subject lang=en>Kinematic Theory of rapid human movements</subject>
<subject lang=en>Sigma-Lognormal model</subject>
<subject>[INFO] Computer Science [cs]</subject>
<type>info:eu-repo/semantics/conferenceObject</type>
<type>Conference papers</type>
<description lang=en>The Sigma-Lognormal model of the Kinematic Theory of rapid human movements allows us to represent on-line signatures with an analytical neuromuscular model. It has been successfully used in the past to generate synthetic signatures in order to improve the performance of an automatic verification system. In this paper, we attempt for the first time to build a verification system based on the model parameters themselves. For describing individual lognormal strokes, we propose eighteen features which capture cognitive psychomotor characteristics of the signer. They are matched by means of dynamic time warping to derive a dissimilarity measure for signature verification. Promising initial results are reported for an experimental evaluation on the SUSIG visual sub-corpus, which contains some of the most skilled forgeries currently available for research.</description>
<date>2015-06-21</date>
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