Graph embedding for offline handwritten signature verification
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2019
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
ICBEA 2019. Proceedings of 2019 3rd International Conference on Biometric Engineering and Applications (ICBEA 2019). Stockholm, Sweden, May 29-31, 2019
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
69-76
Patentnummer
Verlag / Herausgebende Institution
Verlagsort / Veranstaltungsort
Stockholm
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Due to the high availability and applicability, handwritten signatures are an eminent biometric authentication measure in our life. To mitigate the risk of a potential misuse, automatic signature verification tries to distinguish between genuine and forged signatures. Most of the available signature verification approaches make use of vectorial rather than graph-based representations of the handwriting. This is rather surprising as graphs offer some inherent advantages. Graphs are, for instance, able to directly adapt their size and structure to the size and complexity of the respective handwritten entities. Moreover, several fast graph matching algorithms have been proposed recently that allow to employ graphs also in domains with large amounts of data. The present paper proposes to use different graph embedding approaches in conjunction with a recent graph-based signature verification framework. That is, signature graphs are not directly matched with each other, but first compared with a set of predefined prototype graphs, in order to obtain a dissimilarity representation. In an experimental evaluation, we employ the proposed method on two widely used benchmark datasets. On both datasets, we empirically confirm that the learning-free graph embedding outperforms state-of-the-art methods with respect to both accuracy and runtime.
Schlagwörter
Fachgebiet (DDC)
330 - Wirtschaft
Veranstaltung
3rd International Conference on Biometric Engineering and Applications (ICBEA 2019)
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
29.05.2019
Enddatum der Konferenz
31.05.2019
Datum der letzten Prüfung
ISBN
978-1-4503-6305-1
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Closed
Lizenz
Zitation
STAUFFER, Michael, Paul MAERGNER, Andreas FISCHER und Kaspar RIESEN, 2019. Graph embedding for offline handwritten signature verification. In: ICBEA 2019. Proceedings of 2019 3rd International Conference on Biometric Engineering and Applications (ICBEA 2019). Stockholm, Sweden, May 29-31, 2019. Stockholm. 2019. S. 69–76. ISBN 978-1-4503-6305-1. Verfügbar unter: https://irf.fhnw.ch/handle/11654/42554