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Real-time writer verification system using tablet information

使用平板电脑信息的实时作者验证系统

基本信息

批准号：
10650380
负责人：
HANGAI Seiichiro
金额：
$ 2.11万
依托单位：
Science University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1998
资助国家：
日本
起止时间：
1998 至 1999
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10650380/
关键词：
Writer verification Signature verification Identification Online processing Tablet

项目摘要

In this research, we investigated a new on-line signature verification method. which uses the pen movement. We adopt altitude and direction variation of pen movement as parameter to extract the individuality of signatures. All signature data obtained by the tablet are preprocessed. They are normalized by the length of writing duration, which is decided by magnitude of the pen pressure. In the following experiments, we use three data sets, they are pen movement, shape of signature and writing pressure.In general, there is some fluctuations of the data set in the time-axis when a person writes his signatures. We compare the results of normal linear matching method and the DP matching method. In our method, the correct verification rate is independently evaluated by using each of three data sets which are pen movement, shape of signature and writing pressure. The correct verification rate is decided by the point where the accepted percentage of genuine signatures and the rejected percentage of mimicked signatures are balanced.From experimental results with 24 writers, following verification rates are obtained.1)linear matching methodshape of signature : 72.4% / writing pressure : 77.0% / pen movement : 90.3%2)DP matching methodshape of signature : 73.2% / writing pressure : 79.9% / pen movement : 91.3%Although most of conventional signature verification methods utilize the signature shape and writing pressure, it is verified that the pen movement with DP matching is very effective compared to such parameters.

在本研究中，我们研究了一种新的在线签名验证方法。它使用的是笔的移动。我们采用笔迹运动的高度和方向变化作为特征参数来提取签名的个性。通过平板获得的所有签名数据都经过了预处理。它们通过书写持续时间的长度进行标准化，而书写持续时间由钢笔压力的大小决定。在接下来的实验中，我们使用了三个数据集，分别是笔的移动、签名的形状和书写压力，一般情况下，当一个人写签名时，数据集在时间轴上会有一些波动。比较了常规线性匹配法和DP匹配法的匹配结果。在我们的方法中，通过使用笔的移动、签名的形状和书写压力这三个数据集中的每一个独立地评估正确验证率。验证正确率取决于真伪签名接受率和拒绝签名率的平衡点。通过对24名写信人的实验结果，得到如下验证率：1)线性匹配法签名形状：72.4%/书写压力：77.0%/笔移动：90.3%2)DP匹配方法签名形状：73.2%/书写压力：79.9%/笔移动：91.3%虽然大多数传统的签名验证方法利用了签名形状和书写压力，但实验证明，与这些参数相比，DP匹配的笔移动是非常有效的。