Time-series averaging and local stability-weighted dynamic time warping for online signature verification
Time-series averaging and local stability-weighted dynamic time warping for online signature verification
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DOI：
10.1016/j.patcog.2020.107699
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发表时间：
2021-01-30
影响因子：
8
通讯作者：
Okawa, Manabu
中科院分区：
文献类型：
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作者：
Okawa, Manabu
为了满足自动安全系统的最新需求，本研究提出了一种新的单模板策略，使用平均模板和局部稳定加权动态时间规整（LS-DTW），同时提高在线签名验证的速度和准确性。具体来说，我们采用最近的时间序列平均方法，称为基于欧几里德重心的DTW重心平均（EB-DBA），以获得有效的平均模板集为每个功能，同时保留用户内的参考样本之间的变化。然后，我们估计的平均模板集的局部稳定性，通过使用直接匹配点，代表稳定的签名区域之间的DTW翘曲路径的平均模板集和参考。随后，我们在验证阶段使用LS-DTW距离度量来提高区分能力，该距离度量将局部稳定性序列作为平均模板集和查询签名之间的DTW成本函数的权重。最后，使用公开的SVC 2004 Task 2/MCYT-10 0在线签名数据集和最新的3DAirSig空中签名数据集进行实验，实验结果证实了该方法在随机和熟练伪造场景下的有效性. (C)2020爱思唯尔有限公司保留所有权利。
To meet the recent demands for automated security systems, this study proposes a novel single-template strategy that uses mean templates and local stability-weighted dynamic time warping (LS-DTW) to simultaneously improve the speed and accuracy of online signature verification. Specifically, we adopt a recent time-series averaging method, called Euclidean barycenter-based DTW barycenter averaging (EB-DBA), to obtain an effective mean template set for each feature while preserving intra-user variability among reference samples. We then estimate the local stability of the mean template set by using direct matching points that represent stable signature regions in the DTW warping paths between the mean template set and the references. Subsequently, we boost the discriminative power in the verification phase using the LS-DTW distance measure that incorporates the local stability sequence as the weights for the DTW cost function between the mean template set and a query signature. Finally, we use the public SVC2004 Task2/MCYT-10 0 online signature datasets and the recent 3DAirSig in-air signature dataset to conduct experiments, whose results confirm the effectiveness of the proposed method in both the randomand skilled-forgery scenarios. (C) 2020 Elsevier Ltd. All rights reserved.