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International Journal on Document Analysis and Recognition (IJDAR)
Published in: International Journal on Document Analysis and Recognition (IJDAR) 1/2019

11-02-2019 | Original Paper

Online signature verification based on string edit distance

Authors: Kaspar Riesen, Roman Schmidt

Published in: International Journal on Document Analysis and Recognition (IJDAR) | Issue 1/2019

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Abstract

Handwritten 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.
previous article Stroke order normalization for improving recognition of online handwritten mathematical expressions
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Footnotes
1
Multimodal systems combine algorithms from different categories.
 
2
Often the DTW algorithm is endowed with a Sakoe–Chiba band [24] in order to exclude unusual warping paths and speed up the computation.
 
3
The Euclidean distance could be replaced by any other Minkowski metric
 
4
We perform our evaluation on a 3.5 GHz Intel Core i7 with 16 GB RAM.
 
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Metadata
Title
Online signature verification based on string edit distance
Authors
Kaspar Riesen
Roman Schmidt
Publication date
11-02-2019
Publisher
Springer Berlin Heidelberg
Published in
International Journal on Document Analysis and Recognition (IJDAR) / Issue 1/2019
Print ISSN: 1433-2833
Electronic ISSN: 1433-2825
DOI
https://doi.org/10.1007/s10032-019-00316-1

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