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Computer based face recognition using neural networks: A biometric access control system based on the human face.

机译:使用神经网络的基于计算机的面部识别:一种基于人脸的生物特征访问控制系统。

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摘要

Fraud is faced on a daily basis in today's society. An impostor could slip through and access highly sensitive locations, a child could be released to a stranger from a daycare center, a welfare recipient could sign up for benefits under six identities, a voter may vote under two different names using two different social security numbers, and a counterfeiter could make copies of and charges to credit cards. Authentic means of identity verification are urgently in high demand. Biometrics, which is the field that incorporates the measurement of one or more distinctive biological trait(s) in order to be studied, examined, or used to uniquely identify its owner, is the most promising solution.; A biometric system that employs the human face for identity verification and access control was successfully developed and tested. In the course of achieving this goal, two different models were developed and tested. One employs a neural network and the other uses feature extraction by implementing a novel elastic template matching approach.; The neural network based model was considered for further development and modification to build the aimed system. The developed face based biometric access control system incorporates more than one access control technique in order to provide a higher level of security. The system employs the user's knowledge of a password or personal identification number (PIN), possession of a magnetic strip card providing the user's name, and the user's face as a physiological characteristic in order to grant or deny access. The results obtained after rigorous testing of the system are very encouraging.
机译:在当今社会,欺诈行为每天都面临着。冒名顶替者可能会溜进并进入高度敏感的地点,儿童可能会从日托中心被释放给陌生人,福利接收者可以使用六个身份签署福利申请,选民可以使用两个不同的社会安全号码以两个不同的名字投票,并且造假者可以复制信用卡并从中收取费用。迫切需要真实的身份验证手段。最有希望的解决方案是生物测定学,该领域结合了对一种或多种独特生物特征的测量,以便进行研究,检验或用于唯一地识别其所有者。成功开发并测试了使用人脸进行身份验证和访问控制的生物识别系统。在实现这一目标的过程中,开发并测试了两种不同的模型。一种采用神经网络,另一种则通过实施一种新颖的弹性模板匹配方法来使用特征提取。考虑了基于神经网络的模型,以进一步开发和修改以构建目标系统。所开发的基于面部的生物特征访问控制系统结合了不止一种访问控制技术,以提供更高级别的安全性。该系统利用用户的密码或个人识别码(PIN)知识,拥有提供用户名的磁条卡以及用户的脸部作为生理特征来授予或拒绝访问权限。在对系统进行严格测试后获得的结果令人鼓舞。

著录项

  • 作者

    Altaf, Usamah M. S.;

  • 作者单位

    University of Missouri - Rolla.;

  • 授予单位 University of Missouri - Rolla.;
  • 学科 Engineering Electronics and Electrical.; Artificial Intelligence.
  • 学位 Ph.D.
  • 年度 1996
  • 页码 140 p.
  • 总页数 140
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;人工智能理论;
  • 关键词

  • 入库时间 2022-08-17 11:49:14

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