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Facial Image Verification for Government Kiosk System

机译:政府售货亭系统的面部图像验证

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摘要

Some government organizations have been started mega-projects from which Thai citizens can access their welfare data and receive services from the government via kiosk machines. The kiosk machines are typically installed at the government offices and public places. To access any data or services, the user authentication is done by the Thai citizen smart ID card. However, the weakness of the current system is person verification; it is possible that someone uses the other’s ID card. In this paper, we propose a facial image verification system prototype that can integrate to the existing well-fare kiosks. The face verification is done by comparing the face image retrieved from the smart ID card and the face image taken from a camera on the kiosk. The prototype system aims to cross-check the ownership of the smart card holder and to protect personal data privacy. We implemented Face Verification APIs based on the ResNet and MobileNet. From the experimental results, when tested with Cross-Age LFW face dataset, the accuracies are 99.996% and 99.988% on the ResNet50 and the MobileNet, respectively. However, the accuracies reduce to 96.296% and 95.556% when tested on the low-quality face images that embedded in the national ID cards. The system is designed as a client-server model using Microservices Architecture (MSA) style that complements “loosely coupled” multiple services which can be leveraged to share important functionality throughout other government agencies.
机译:一些政府机构已经开始从泰国公民可以从政府通过公共计算机上访问他们的福利数据和接收服务大型项目。售货亭机器通常安装在政府办公室和公共场所。要访问任何数据或服务,用户身份验证由泰国公民智能身份证完成。但是,目前系统的弱点是人核实;有人可能使用其他的身份证。在本文中,我们提出了一个面部图像验证系统原型,可以集成到现有的胜利售货亭。通过比较从智能ID卡和从亭子上的相机拍摄的面部图像来进行面部验证来完成。原型系统旨在交叉检查智能卡持有人的所有权并保护个人数据隐私。我们基于Reset和MobileNet实现了面部验证API。从实验结果,当用次龄LFW面部数据集进行测试时,分别在Reset50和Mobilenet上的精度为99.996%和99.988%。然而,在嵌入国籍身份证的低质量脸部图像上测试时,精度降低至96.296%和95.556%。该系统设计为使用微服务架构(MSA)风格的客户端 - 服务器模型,这些架构可以使用“松散耦合”多项服务,这些服务可以利用,以便在整个其他政府机构中共享重要功能。

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