Efficient on-line signature verification system

In this paper, a robust automatic on-line signature verification system is proposed. The effectiveness of any on-line signature verification system depends mainly on the robustness of the dynamic features use in the system. Inability to extract highly discriminative dynamic features from signature has been contributing to higher verification error-rates. On-line signature verification experiments are conducted on seven dynamic signature features extracted from signature trajectories. Three features are found to be highly discriminative in comparison with others. The proposed system incorporates these three features for signature verification. Verification is based on the average of all the distances obtain from the cross-alignment of the features. The proposed system is tested with quality signature samples and it has 0.5% error in rejecting skilled forgeries while rejecting only 0.25% of genuine signatures. These results are better in comparison with the results obtained from previous systems