Evaluation of features and normalization techniques for signature verification using dynamic time warping

This paper examines the use of different feature sets and normalization techniques for a signature and password verifier. The verifier made use of the Dynamic Time Warping (DTW) algorithm. Features that incorporated the pen velocity were found to be the strongest performers in tests against informed forgeries. Overall, password verification did not perform as well as signature verification. On average, the equal error rate for passwords was 2.7% higher than for signatures. Most signature and password features achieved their best performance when they were power-normalized, although normalization in both time and power was sometimes beneficial as well.