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

Rami Al-Hmouz*, Witold Pedrycz, Khaled Daqrouq, Ali Morfeq, Ahmed Al-Hmouz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)407-418
Number of pages12
JournalSoft Computing
Volume23
Issue number2
DOIs
Publication statusPublished - Jan 30 2019
Externally publishedYes

Keywords

  • Dynamic signature
  • Dynamic time warping
  • Multimodal identification

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Geometry and Topology

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