EURASIP Journal on Applied Signal Processing
A writer identification system for on-line whiteboard data
Pattern Recognition
Rough set approach to online signature identification
Digital Signal Processing
A survey of on-line signature verification
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
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Abstract: This paper investigates dynamic handwritten signature verification (HSV) using the wavelet transform with verification by the backpropagation neural network (NN). It is yet another avenue in the approach to HSV that is found to produce excellent results when compared with other methods of dynamic, or on-line, HSV. Using a database of dynamic signatures collected from 41 Chinese writers and 7 from Latin script we extract features (including pen pressure, x and y velocity, angle of pen movement and angular velocity) from the signature and apply the Daubechies-6 wavelet transform using coefficients as input to a NN which learns to verify signatures with a False Rejection Rate (FRR) of 0.0% and False Acceptance Rate (FAR) less of than 0.1%.