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Motion-Activated Facial Recognition-Based Electronic Residential Logbook using PCA Algorithm with Web Application

机译:基于PCA算法和Web应用的基于运动激活面部识别的电子住宅日志

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This paper embarks on the development of an electronic residential logbook that is motion-activated and utilizes facial recognition as its biometrics authentication. This paper aims to access log information through a web application. The algorithm that was used for the facial recognition process is known as the Principal Component Analysis, a linear technique that is widely used in recognition and compression applications. Moreover, an application of PCA which is the Eigenface technique was used in capturing the most necessary factor in the facial recognition process. The hardware part of the electronic residential logbook is driven by AT89S52 microcontroller where a PIR sensor is connected. The PIR sensor is responsible for the motion activation of this design. The log record information can be viewed through a web application which reflects the time in/out of the residents. In conclusion, the researchers were able to meet all of their objectives and provided the expected output with a 13% error rate for the facial recognition system with only 5 training faces conducted for each resident.
机译:本文着手开发一种可运动激活并利用面部识别作为其生物特征认证的电子住宅日志。本文旨在通过Web应用程序访问日志信息。用于面部识别过程的算法称为“主成分分析”,这是一种线性技术,广泛用于识别和压缩应用程序。此外,作为特征脸技术的PCA的应用被用于捕获面部识别过程中最必要的因素。电子住宅日志的硬件部分由连接了PIR传感器的AT89S52微控制器驱动。 PIR传感器负责激活此设计。可以通过Web应用程序查看日志记录信息,该应用程序反映居民进出的时间。总之,研究人员能够实现他们的所有目标,并为面部识别系统提供了预期的输出,错误率达到13%,每个居民仅进行了5张训练面部的训练。

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