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Improving facial recognition accuracy by applying liveness monitoring technique

机译:通过使用动态监控技术提高面部识别的准确性

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In a typical transmission control protocol and Internet protocol (TCP/IP) suite, there are several ways, such as using photograph, three-dimensional (3D) model, and video clip of a valid user to mock the facial recognition. Studies show that there has been significant improvement in detecting photograph and 3D model spoofing. However, there is no such improvement in detecting video spoofing. Recent studies suggest that liveness monitoring using the facial features has potential to improve security, especially in biometric systems. In this paper, a liveness monitoring technique is introduced to assist facial recognition. In the proposed system, an eye blinking pattern is used through a real-time generic web-camera. An eye blinking password system using ultrasonic range sensing module is developed for liveness detection of the users. The system is tested by conducting experiments using 15 valid users and 100 different user appearances. According to the experimental results, the proposed system achieves 99% face recognition accuracy and 99% liveliness detection performance.
机译:在典型的传输控制协议和Internet协议(TCP / IP)套件中,有几种方法,例如使用照片,三维(3D)模型和有效用户的视频剪辑来模拟面部识别。研究表明,在检测照片和3D模型欺骗方面有了显着的进步。但是,在检测视频欺骗方面没有这样的改进。最近的研究表明,使用面部特征进行活动监视具有改善安全性的潜力,尤其是在生物识别系统中。在本文中,介绍了一种活动性监视技术来辅助面部识别。在提出的系统中,通过实时通用网络摄像机使用眨眼模式。开发了一种使用超声波测距模块的眨眼密码系统,用于检测用户的生命。通过使用15个有效用户和100个不同用户外观进行实验来测试该系统。根据实验结果,提出的系统实现了99%的人脸识别精度和99%的生动度检测性能。

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