access icon free A robust dissimilarity representation for writer-independent signature modelling

© The Institution of Engineering and Technology
Received 25/01/2013, Accepted 28/05/2013, Revised 11/04/2013, Published

In this study, the authors present a novel dissimilarity-based signature modelling framework for writer-independent off-line signature verification. The proposed framework utilises a discrete Radon transform and a dynamic time warping algorithm for writer-independent signature representation in dissimilarity space, and a writer-specific strategy for dissimilarity normalisation. A discriminative classifier, either a discriminant function or a support vector machine, is utilised for verification purposes. Both linear and non-linear decision boundaries are considered. The authors show that the novel techniques presented in this study provide an improved platform for writer-independent signature modelling. When evaluated on Dolfing's data set, a signature database that contains 1530 genuine signatures and 3000 amateur skilled forgeries, the systems presented in this study outperform all previous systems also evaluated on this data set.

Inspec keywords: Radon transforms; support vector machines; digital signatures; image representation; image classification; discrete transforms; handwriting recognition

Other keywords: dynamic time warping algorithm; discriminative classifier; dissimilarity-based signature modelling; dissimilarity representation; support vector machine; writer-independent signature representation; Dolfing data set; discrete Radon transform; dissimilarity normalisation; signature database; nonlinear decision boundary; dissimilarity space; writer-independent offline signature verification; writer specific strategy; discriminant function; linear decision boundary

Subjects: Integral transforms; Image recognition; Computer vision and image processing techniques; Integral transforms; Data security; Cryptography

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