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Quantifying dynamic time warping distance using probabilistic model in verification of dynamic signatures

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Abstract

One of the multimodal biometric scenarios is realized by considering several features coming from a single biometric entity. Dynamic signature verification has been utilized considering such scenarios. We present a new approach, namely probabilistic dynamic time warping, to verify dynamic signatures where we use dynamic time warping in realizing distance determination in the verification process. Signatures are segmented into several segments, where probability of each segment is quantified with the aid of a relative distance associated with two selected threshold levels. The final decision is achieved by combining all segment probabilities using a Bayes rule. Experiments demonstrate improvement of equal error rate for the proposed approach for the random forgery. The method has been tested on synthetic dataset and two publicly available databases of dynamic signatures, namely SCV2004 and MCYT100.

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Acknowledgements

This project was funded by the National Plan for Science, Technology and Innovation (MAARIFAH)—King Abdulaziz City for Science and Technology—the Kingdom of Saudi Arabia—award number (12-INF3105-03). The authors also acknowledge with thanks Science and Technology Unit, King Abdulaziz University, for technical support.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Rami Al-Hmouz, Witold Pedrycz, Khaled Daqrouq & Ali Morfeq

  2. Department of Electrical & Computer Engineering, University of Alberta, Edmonton, AB, T6R 2V4, Canada

    Witold Pedrycz

  3. Department of Information Technology, Middle East University, Amman, Jordan

    Ahmed Al-Hmouz

Authors
  1. Rami Al-Hmouz
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  2. Witold Pedrycz
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  3. Khaled Daqrouq
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  4. Ali Morfeq
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  5. Ahmed Al-Hmouz
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Correspondence to Rami Al-Hmouz.

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The authors declare that they have no conflict of interest.

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Communicated by V. Loia.

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Al-Hmouz, R., Pedrycz, W., Daqrouq, K. et al. Quantifying dynamic time warping distance using probabilistic model in verification of dynamic signatures. Soft Comput 23, 407–418 (2019). https://doi.org/10.1007/s00500-017-2782-5

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  • DOI: https://doi.org/10.1007/s00500-017-2782-5

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