Quantifying dynamic time warping distance using probabilistic model in verification of dynamic signatures
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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.
KeywordsMultimodal identification Dynamic signature Dynamic time warping
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.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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