Modified Dynamic Time Warping with Local and Global Weighting for Online Signature Verification
Modified Dynamic Time Warping with Local and Global Weighting for Online Signature Verification
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DOI：
10.1109/lifetech52111.2021.9391879
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Manabu Okawa
中科院分区：
文献类型：
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作者：
Manabu Okawa
本文提出了一种利用局部和全局加权动态时间规整（LG-DTW）提高在线签名验证性能的方法。在登记阶段，我们使用基于欧几里德重心的DTW重心平均获得参考文献之间的平均模板集。我们通过分析平均值模板和参考集之间的直接匹配点来获得用户内部可变性的局部加权估计。我们使用梯度增强计算用户间可变性的全局加权估计。最后，在验证阶段，我们应用局部和全局加权估计来获得查询样本和平均模板集之间的判别性LG-DTW。在公开的SVC2004 Task2数据集上的实验结果证实了该方法的有效性。
This study proposes a novel online signature verification using locally and globally weighted dynamic time warping (LG-DTW) to improve the verification performance. In the enrollment phase, we obtain a mean template set among references using Euclidean barycenter-based DTW barycenter averaging. We acquire a local weighting estimate obtained by analyzing direct matching points between the mean template and reference sets for intra-user variability. We compute a global weighting estimate using gradient boosting for inter-user variability. Finally, in the verification phase, we apply the local and global weighting estimates to acquire a discriminative LG-DTW between a query sample and the mean template set. Experimental results obtained on the public SVC2004 Task2 dataset confirmed the effectiveness of the proposed method.