- Rico-Juan, J. R.; Iņesta, J. M.
"Confidence voting method ensemble applied to off-line signature verification"
Pattern Analysis and Applications, vol. 15, pp. 113--120
In this paper, a new approximation to off-line signature verification is proposed based on two-class classifiers using an expert decisions ensemble. Different methods to extract sets of local and a global features from the target sample are detailed. Also a normalisation by confidence voting method is used in order to decrease the final equal error rate (EER). Each set of features is processed by a single expert, and on the other approach proposed, the decisions of the individual classifiers are combined using weighted votes. Experimental results are given using a subcorpus of the large MCYT signature database for random and skilled forgeries. The results show that the weighted combination outperforms the individual classifiers significantly. The best EER obtained were 6.3% in the case of skilled forgeries and 2.3% in the case of random forgeries.
author = "Rico-Juan, J. R.; Iņesta, J. M.",
title = "Confidence voting method ensemble applied to off-line signature verification",
issn = "1433-7541",
journal = "Pattern Analysis and Applications",
month = "apr",
number = "2",
pages = "113--120",
volume = "15",
year = "2012"