Open AccessA robust dissimilarity representation for writer‐independent signature modelling
Author(s) -
Swanepoel Jacques,
Coetzer Johannes
Publication year - 2013
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2013.0011
Subject(s) - computer science , representation (politics) , signature (topology) , natural language processing , artificial intelligence , information retrieval , pattern recognition (psychology) , data mining , geometry , mathematics , politics , political science , law
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.