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A novel biometric system for signature verification based on score level fusion approach

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Abstract

The active modality of handwriting is broadly related to signature verification in the context of biometric user authentication systems. Signature verification aims to verify a questioned signature as being genuine or forged compared to some previously provided signatures from the claimed person. By doing so, we may be able to verify a person’s identity at accuracy and speed even better than human performance. Application areas of signature verification include different purposes and principally in access controls and forensic document examination. This work presents a novel biometric system for signature verification. We propose a new model that we called the Extended Beta-elliptic model and we integrate the fuzzy elementary perceptual codes (FEPC) to extract static and dynamic features. To discriminate the genuine and forgery signatures of a user, we explore a fusion using the sum rule combiner of three scores which are deep bidirectional long short-term memory (deep BiLSTM), support vector machine (SVM) with Dynamic Time Warping (DTW), and SVM with a new proposed parameter comparator. Our system has been evaluated on two publicly available online signature databases namely SVC2004 Task 2 and MCYT-100, and it shows promising performance gains.

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Acknowledgments

The research leading to these results has received funding from the Ministry of Higher Education and Scientific Research of Tunisia under the grant agreement number LR11ES4.

Funding

This study was funded by the Ministry of Higher Education and Scientific Research of Tunisia (grant number LR11ES4).

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Authors and Affiliations

  1. University of Sousse, ISITCom, 4011, Sousse, Tunisia

    Thameur Dhieb

  2. REsearch Groups in Intelligent Machines (REGIM Lab), University of Sfax, National Engineering School of Sfax (ENIS), BP 1173, 3038, Sfax, Tunisia

    Thameur Dhieb, Houcine Boubaker, Sourour Njah, Mounir Ben Ayed & Adel M. Alimi

  3. High Institute of Commerce of Sfax, University of Sfax, Sfax, Tunisia

    Sourour Njah

  4. Computer Sciences and Communication Department, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia

    Mounir Ben Ayed

  5. Department of Electrical and Electronic Engineering Science, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

    Adel M. Alimi

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  1. Thameur Dhieb
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Correspondence to Thameur Dhieb.

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Dhieb, T., Boubaker, H., Njah, S. et al. A novel biometric system for signature verification based on score level fusion approach. Multimed Tools Appl 81, 7817–7845 (2022). https://doi.org/10.1007/s11042-022-12140-7

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