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基于印记特征的滚筒式日期盖章的品牌识别

Zhenghao Pan¹, Weina Chen¹, Ziyun Tian¹

¹College of Criminal Investigation, People's Public Security University of China, Beijing, China.

Journal of forensic sciences

|March 8, 2026

概括

本研究引入了一种机器学习方法,用于识别中国滚筒式日期邮票的品牌. 该方法使用印花印记的形态特征进行法医分析和品牌认证.

科学领域:

法医科学法医科学法医科学
文件审查文件审查
机器学习应用机器学习应用

背景情况:

滚筒式日期邮票在中国制造业和行政部门广泛使用.
盖章印记在伪造,假冒标签和可追溯性争端的法医案例工作中至关重要.

研究的目的:

制定一个定量框架,用于中国滚筒式日期盖章的品牌识别.
为了利用形态特征提取和机器学习进行邮票分析.

主要方法:

在36个条件下评估了16个商用邮票模型,生成了17280个印记样本.
从中文字符中提取了17个形态特征,用于"年"",月"和"日".
使用间隔重叠率 (IOR) 和主要组件分析 (PCA) 进行特征改进,并使用了四个监督分类器 (GBDT,RF,SVM,NB).

主要成果:

渐变增强决策树 (GBDT) 和随机森林 (RF) 实现了高精度 (96.76%和95.66%在实验室; 89.06%和90.88%在现场).
证明印花印记具有可量化的,品牌特有的形态特征.
验证了数据驱动模型的稳定性和区分能力.

结论:

使用数据驱动的机器学习模型,可以可靠地识别滚筒类型的印记.
拟议的方法为法医品牌识别提供了一个快速,非破坏性和科学稳健的工具.
这种方法在涉及假冒标签和产品可追溯性的案件中增强了证据认证.

关键词:

法医文档检查检查法医文档检查印象形态形态学印象形态学间隔重叠率 (IOR);主要组件分析 (PCA).机器学习是机器学习.一个滚筒式日期盖章.

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