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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.