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.

基于计算模型的书写学习和执行研究结果，我们引入了稳定性的概念来解释被试的签名在多次执行过程中实际运动的差异，并推测在签名验证过程中，签名的最稳定部分应该在评估被质疑签名与参考签名之间的相似性方面起着重要作用。我们随后引入了稳定区域调制动态时间规整算法，将稳定区域（即两个签名之间最相似的部分）纳入由动态时间规整算法计算的一对签名之间的距离度量中，用于签名验证。我们在两个用于性能评估的数据集上进行了实验。实验结果显示，所提出的算法改进了基准系统的性能，并与其他表现优异的签名验证系统相比具有可比性。