Text and User Generic Model for Writer Verification Using Combined Pen Pressure Information From Ink Intensity and Indented Writing on Paper
Text and User Generic Model for Writer Verification Using Combined Pen Pressure Information From Ink Intensity and Indented Writing on Paper
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DOI：
10.1109/thms.2014.2380828
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发表时间：
2015-06-01
影响因子：
3.6
通讯作者：
Yoshida, Kenichi
中科院分区：
文献类型：
--
作者：
Okawa, Manabu;Yoshida, Kenichi
作者验证是一种从笔迹中指定真实作者的方法。各种应用（例如，信用卡、支票和护照）。然而，与人类（例如，法医文件检查员）的表现相比，这种方法的表现还有改进的余地。由于自动化的作者验证系统在任何情况下都不总是返回正确的结果，这可能导致严重的后果，需要进一步的研究来提高这些方法的性能。此外，有限的样本所造成的问题，必须解决真实的应用。为了提高验证精度与有限的样本，我们提出了一个文本和用户通用模型的作家验证，使用的组合笔的压力信息从墨水强度和书写压痕获得的多波段图像扫描仪。我们引入了一个作家特定的相异度表示，考虑个人的笔迹特征，影响模型的性能。本文报告了从54名志愿者收集的笔迹样本的实验结果。结果表明，与传统方法相比，错误率从10.0%下降到4.0%。
Writer verification is a method to specify an authentic writer from handwriting. Automated writer verification methods are required for various applications (e.g., credit cards, checks, and passports). However, there is room for improvement in the performance of such methods compared with the performance of human beings, for example, forensic document examiners. Because automated writer verification systems do not always return correct results under any circumstances, which can lead to grave consequences, further research is required to improve the performance of such methods. Furthermore, problems caused by limited samples must be solved for real applications. To improve verification accuracy with limited samples, we propose a text and user generic model for writer verification that uses a combination of pen pressure information from ink intensity and writing indentations obtained by a multiband image scanner. We introduce a writer-specific dissimilarity representation to consider individual handwriting characteristics that affect model performance. Experimental results obtained using handwriting samples collected from 54 volunteers are reported. The results show a decrease in error rate compared with conventional methods from 10.0% to 4.0%.