SM-DTW: Stability Modulated Dynamic Time Warping for signature verification
This addresses signature verification for authentication, but it is incremental as it builds on existing dynamic time warping methods.
The paper tackles signature verification by introducing stability-modulated dynamic time warping, which focuses on the most stable parts of signatures to improve similarity evaluation. Experimental results on two datasets show it improves baseline performance and compares favorably with other top systems.
Building upon findings in computational model of handwriting learning and execution, we introduce the concept of stability to explain the difference between the actual movements performed during multiple execution of the subject's signature, and conjecture that the most stable parts of the signature should play a paramount role in evaluating the similarity between a questioned signature and the reference ones during signature verification. We then introduce the Stability Modulated Dynamic Time Warping algorithm for incorporating the stability regions, i.e. the most similar parts between two signatures, into the distance measure between a pair of signatures computed by the Dynamic Time Warping for signature verification. Experiments were conducted on two datasets largely adopted for performance evaluation. Experimental results show that the proposed algorithm improves the performance of the baseline system and compares favourably with other top performing signature verification systems.