身份证和旅行证件的综合数据集
Carlos Boned1, Maxime Talarmain1, Nabil Ghanmi2
1Computer Vision Centre, Bellaterra, 08193, Spain.
Scientific data
|December 18, 2024
概括
创建了一个新的识别 (ID) 和旅行文件的合成数据集,称为SIDTD,用于训练和评估伪造文件检测系统. 这一数据集解决了真正伪造文件的稀缺问题,并帮助在线登陆中自动验证身份证件.
科学领域:
- 计算机视觉 计算机视觉
- 文档图像分析 文档图像分析
- 机器学习 机器学习
背景情况:
- 由于个人信息隐私问题,真实身份证 (ID) 和旅行证件的公共数据集是不可行的.
- 检测伪造的文件是具有挑战性的,因为真正的伪造例子的稀缺性和伪造方法的高内部变化.
- 现有的在线登陆中自动身份验证系统需要强大的培训数据.
研究的目的:
- 引入一个新的合成数据集,SIDTD (合成身份证和旅行证件),用于培训和评估伪造身份证件检测系统.
- 模拟 ID 和旅行证件的常见和容易制作的伪造.
- 推进文档图像分析领域的自动身份验证.
主要方法:
- 采用合成数据生成技术,创建多样化的身份证和旅行证件数据集.
- 数据集中于模拟最常见和可访问的伪造类型.
- 生成过程解释了在欺诈性文件中经常出现的变化.
主要成果:
- SIDTD数据集为文档分析领域的研究人员和开发人员提供了宝贵的资源.
- 它允许训练和对测试用于检测伪造身份证和旅行证件的算法.
- 合成性质允许控制生成和增强伪造的例子.
结论:
- SIDTD数据集是提高自动身份证件验证系统的准确性和可靠性的关键一步.
- 它通过为伪造检测提供急需的培训资源,促进了文档图像分析的进步.
- 这一合成数据集将有助于开发更安全的在线登陆流程.
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