Online Signature Verification Using Locally Weighted Dynamic Time Warping via Multiple Fusion Strategies
Online Signature Verification Using Locally Weighted Dynamic Time Warping via Multiple Fusion Strategies
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DOI：
10.1109/access.2022.3167413
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发表时间：
2022
期刊：
影响因子：
3.9
通讯作者：
Manabu Okawa
中科院分区：
文献类型：
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作者：
Manabu Okawa
采用动态签名验证系统来验证作者身份的过程被称为在线签名验证。例如，它可以用作验证入口应用程序和密码替代品的安全系统，也可以用作支持专家调查的取证工具。本文提出了一种基于单模板策略的在线签名验证系统，以提高真实场景下的签名验证性能。它使用的歧视性的平均签名模板集，以及融合策略的多个局部加权和翘曲计划的动态时间规整（DTW）。首先，使用最近的时间序列平均方法为每个特征创建一组用户特定的平均签名模板，即，基于欧氏重心的DTW重心平均。然后，我们获得一个局部加权估计，考虑局部稳定序列的基础上的多个和直接匹配点之间的平均签名模板和参考依赖和独立DTW。此外，我们推导出融合策略来计算局部加权DTW集，并将它们连接为每个翘曲的特征向量，然后分别构建支持向量机（SVM）分类器。最后，在验证阶段，我们采用单模板技术来获得一个判别融合得分使用SVM之间的平均模板集和查询样本。利用三个公共在线签名数据集（SVC 2004 Task 1/Task 2和MCYT-100）获得的大量实验结果证明了所提出方法的有效性。
The process of employing a dynamic signature verification system to verify the writer’s identity is known as online signature verification. It can be used as a security system to verify entrance applications and password substitutes, and as a forensic tool to support expert’s investigation, for example. This study proposes a novel online signature verification system based on a single-template strategy to improve performance in real-world scenarios. It uses discriminative mean signature template sets as well as fusion strategies of multiple local weighting and warping schemes for dynamic time warping (DTW). First, there is the creation of a set of user-specific mean signature templates for each feature using a recent time-series averaging method, i.e., Euclidean barycenter-based DTW barycenter averaging. Then, we acquire a local weighting estimate considering local stability sequences based on multiple and direct matching points between the mean signature templates and references for dependent and independent DTW. Moreover, we derive fusion strategies to calculate locally weighted DTW sets and concatenate them as a feature vector for each warping, followed by constructing a support vector machine (SVM) classifier, respectively. Finally, in the verification phase, we employ the single-template technique to obtain a discriminative fused score using SVMs between the mean template sets and a query sample. The suggested method’s efficiency is demonstrated by extensive experimental results acquired utilizing three public online signature datasets: SVC2004 Task1/Task2, and MCYT-100.