Abstract
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.
Abstract (translated)
在基于手写学习与执行计算模型的研究基础上，我们引入了稳定性的概念来解释在多次执行主题签名时实际执行动作之间的差异，并推测签名验证过程中，签名中最稳定的部分应发挥关键作用。接着，我们引入了稳定性 modulated Dynamic Time Warping（SM-DTW）算法，用于将稳定区域（即两个签名之间最相似的部分）纳入到由签名验证中的动态时间平移计算得到的签名对之间的距离度量中。我们对两个广泛用于性能评估的数据集进行了实验，实验结果表明，与基线系统相比，所提出的算法在性能上进行了显著改进，且与其它表现优秀的签名验证系统相比具有竞争力的优势。
URL
https://arxiv.org/abs/2405.11978
