动态签名:分析的数学方法
Jessica Baleiro Okado1, Erick Simões da Camara E Silva2, Priscila Dias Sily2
1Institute of Criminalistics, Superintendence of the Technical-Scientific Police, Team Santos, São Paulo, Brazil.
Forensic sciences research
|January 20, 2025
概括
这项研究引入了诸如主要组件分析和动态时间扭曲等数学工具,以客观地分析动态签名,提高真实和模拟样本的手写检查准确性.
科学领域:
- 法医科学 法医科学 法医科学
- 数据分析 数据分析
- 生物识别信息 生物识别信息
背景情况:
- 手写检查传统上依赖于主观分析.
- 在法医文档检查中,需要客观和可重复的方法.
- 动态签名分析提供了丰富的数据来源,超出了静态特征.
研究的目的:
- 评估用于客观分析动态签名的数学工具.
- 为了减少主观性,提高手写检查的可复制性.
- 评估签名验证的两步数学方法的准确性.
主要方法:
- 使用主要组件分析 (PCA) 来获得全球签名数据.
- 使用动态时间扭曲 (DTW) 来进行局部特征特征分析.
- 应用科尔莫戈罗夫-斯米尔诺夫假设测试与优化的P值值 (1x10^-10).
主要成果:
- 实现了高准确率:真正的全球数据为96.7%,模拟的全球数据为88.9%.
- 实现了真实本地数据的平均准确率为95.4%,模拟本地数据的平均准确率为94.7%.
- 该方法显示了伪装签名的局限性,与传统的考试挑战保持一致.
结论:
- 拟议的两步数学方法显著提高了签名分析中的客观性和可重复性.
- 该方法在真实和模拟签名方面具有很高的准确性,适合法医应用.
- 专家可视化和分析与自动化工具一起仍然至关重要.
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