Online signature verification based on string edit distance


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.

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  1. 1.

    Multimodal systems combine algorithms from different categories.

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    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. 3.

    The Euclidean distance could be replaced by any other Minkowski metric

  4. 4.

    We perform our evaluation on a 3.5 GHz Intel Core i7 with 16 GB RAM.


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We would like to thank Prof. Dr. Andreas Fischer for his valuable comments and help on the DTW reference system.

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Correspondence to Kaspar Riesen.

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This work has been supported by the Commission for Technology and Innovation (CTI) project Nr. 18029.1 PFES-ES and the Bern Economic Development Agency.

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Riesen, K., Schmidt, R. Online signature verification based on string edit distance. IJDAR 22, 41–54 (2019).

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  • User authentication
  • Signature verification
  • String matching
  • String edit distance