Combining graph edit distance and triplet networks for offline signature verification
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Authors
Maergner, Paul
Pondenkandath, Vinaychandran
Alberti, Michele
Liwicki, Marcus
Ingold, Rolf
Fischer, Andreas
Author (Corporation)
Publication date
2019
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Type
01A - Journal article
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Parent work
Pattern Recognition Letters
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DOI of the original publication
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Series
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Volume
125
Issue / Number
Pages / Duration
527-533
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Publisher / Publishing institution
Elsevier
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Abstract
Offline signature verification is a challenging pattern recognition task where a writer model is inferred using only a small number of genuine signatures. A combination of complementary writer models can make it more difficult for an attacker to deceive the verification system. In this work, we propose to combine a recent structural approach based on graph edit distance with a statistical approach based on deep triplet networks. The combination of the structural and statistical models achieve significant improvements in performance on four publicly available benchmark datasets, highlighting their complementary perspectives.
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Subject (DDC)
330 - Wirtschaft
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ISSN
0167-8655
Language
English
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Yes
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Publication status
Published
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Closed
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Citation
MAERGNER, Paul, Vinaychandran PONDENKANDATH, Michele ALBERTI, Marcus LIWICKI, Kaspar RIESEN, Rolf INGOLD und Andreas FISCHER, 2019. Combining graph edit distance and triplet networks for offline signature verification. Pattern Recognition Letters. 2019. Bd. 125, S. 527–533. DOI 10.1016/J.PATREC.2019.06.024. Verfügbar unter: https://irf.fhnw.ch/handle/11654/42552