Offline Signature Verification Using the Discrete Radon Transform and a Hidden Markov Model

  • J. Coetzer1Email author,

    Affiliated with

    • B. M. Herbst1 and

      Affiliated with

      • J. A. du Preez2

        Affiliated with

        EURASIP Journal on Advances in Signal Processing20042004:925026

        DOI: 10.1155/S1110865704309042

        Received: 31 October 2002

        Published: 21 April 2004

        Abstract

        We developed a system that automatically authenticates offline handwritten signatures using the discrete Radon transform (DRT) and a hidden Markov model (HMM). Given the robustness of our algorithm and the fact that only global features are considered, satisfactory results are obtained. Using a database of 924 signatures from 22 writers, our system achieves an equal error rate (EER) of 18% when only high-quality forgeries (skilled forgeries) are considered and an EER of 4.5% in the case of only casual forgeries. These signatures were originally captured offline. Using another database of 4800 signatures from 51 writers, our system achieves an EER of 12.2% when only skilled forgeries are considered. These signatures were originally captured online and then digitally converted into static signature images. These results compare well with the results of other algorithms that consider only global features.

        Keywords and phrases

        offline signature verification discrete Radon transform hidden Markov model

        Authors’ Affiliations

        (1)
        Department of Applied Mathematics, University of Stellenbosch
        (2)
        Department of Electrical and Electronic Engineering, University of Stellenbosch

        Copyright

        © Coetzer et al. 2004