Online signature verification based on string edit distance

dc.contributor.authorRiesen, Kaspar
dc.contributor.authorSchmidt, Roman
dc.date.accessioned2024-03-20T08:11:55Z
dc.date.available2024-03-20T08:11:55Z
dc.date.issued2019
dc.description.abstractHandwritten signatures are widely used and well-accepted biometrics for personal authentication. The accuracy of signature verification systems has significantly improved in the last decade, making it possible to rely on machines in particular cases or to support human experts. Yet, based on only few genuine references, signature verification is still a challenging task. The present paper provides a comprehensive comparison of two prominent string matching algorithms that can be readily used for signature verification. Moreover, it evaluates a recent cost model for string matching which turns out to be particularly well suited for the task of signature verification. On three benchmarking data sets, we show that this model outperforms the two standard models for string matching with statistical significance.
dc.identifier.doi10.1007/s10032-019-00316-1
dc.identifier.issn1433-2825
dc.identifier.issn1433-2833
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/42431
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofInternational Journal on Document Analysis and Recognition
dc.subject.ddc330 - Wirtschaft
dc.titleOnline signature verification based on string edit distance
dc.type01A - Beitrag in wissenschaftlicher Zeitschrift
dc.volume22
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutInstitut für Wirtschaftsinformatikde_CH
fhnw.openAccessCategoryClosed
fhnw.pagination41-54
fhnw.publicationStatePublished
relation.isAuthorOfPublicationd761e073-1612-4d22-8521-65c01c19f97a
relation.isAuthorOfPublication.latestForDiscoveryd761e073-1612-4d22-8521-65c01c19f97a
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