Signature verification: A comprehensive study of the hidden signature method

Joanna Putz-Leszczyńska

International Journal of Applied Mathematics and Computer Science (2015)

  • Volume: 25, Issue: 3, page 659-674
  • ISSN: 1641-876X

Abstract

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Many handwritten signature verification algorithms have been developed in order to distinguish between genuine signatures and forgeries. An important group of these methods is based on dynamic time warping (DTW). Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures. The right selection of template signatures has a big impact on that verification. In this article, we describe our proposition for replacing the template signatures with the hidden signature-an artificial signature which is created by minimizing the mean misalignment between itself and the signatures from the enrollment set. We present a few hidden signature estimation methods together with their comprehensive comparison. The hidden signature opens a number of new possibilities for signature analysis. We apply statistical properties of the hidden signature to normalize the error signal of the verified signature and to use the misalignment on the normalized errors as a verification basis. A result, we achieve satisfying error rates that allow creating an on-line system, ready for operating in a real-world environment.

How to cite

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Joanna Putz-Leszczyńska. "Signature verification: A comprehensive study of the hidden signature method." International Journal of Applied Mathematics and Computer Science 25.3 (2015): 659-674. <http://eudml.org/doc/271786>.

@article{JoannaPutz2015,
abstract = {Many handwritten signature verification algorithms have been developed in order to distinguish between genuine signatures and forgeries. An important group of these methods is based on dynamic time warping (DTW). Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures. The right selection of template signatures has a big impact on that verification. In this article, we describe our proposition for replacing the template signatures with the hidden signature-an artificial signature which is created by minimizing the mean misalignment between itself and the signatures from the enrollment set. We present a few hidden signature estimation methods together with their comprehensive comparison. The hidden signature opens a number of new possibilities for signature analysis. We apply statistical properties of the hidden signature to normalize the error signal of the verified signature and to use the misalignment on the normalized errors as a verification basis. A result, we achieve satisfying error rates that allow creating an on-line system, ready for operating in a real-world environment.},
author = {Joanna Putz-Leszczyńska},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {verification; on-line recognition; time warping; hidden signature; online recognition},
language = {eng},
number = {3},
pages = {659-674},
title = {Signature verification: A comprehensive study of the hidden signature method},
url = {http://eudml.org/doc/271786},
volume = {25},
year = {2015},
}

TY - JOUR
AU - Joanna Putz-Leszczyńska
TI - Signature verification: A comprehensive study of the hidden signature method
JO - International Journal of Applied Mathematics and Computer Science
PY - 2015
VL - 25
IS - 3
SP - 659
EP - 674
AB - Many handwritten signature verification algorithms have been developed in order to distinguish between genuine signatures and forgeries. An important group of these methods is based on dynamic time warping (DTW). Traditional use of DTW for signature verification consists in forming a misalignment score between the verified signature and a set of template signatures. The right selection of template signatures has a big impact on that verification. In this article, we describe our proposition for replacing the template signatures with the hidden signature-an artificial signature which is created by minimizing the mean misalignment between itself and the signatures from the enrollment set. We present a few hidden signature estimation methods together with their comprehensive comparison. The hidden signature opens a number of new possibilities for signature analysis. We apply statistical properties of the hidden signature to normalize the error signal of the verified signature and to use the misalignment on the normalized errors as a verification basis. A result, we achieve satisfying error rates that allow creating an on-line system, ready for operating in a real-world environment.
LA - eng
KW - verification; on-line recognition; time warping; hidden signature; online recognition
UR - http://eudml.org/doc/271786
ER -

References

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