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Study of automated face recognition system for office door access control application

机译:办公门禁自动人脸识别系统的研究

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The security currently become a very important issue in public or private institutions in which various security systems have been proposed and developed for some crucial processes such as person identifications, verification or recognition especially for building access control, suspect identifications by the police, driver licenses and many others. Face recognitions have been an active area of research with numerous applications since late 1980s and become one of the important elements in security system development. This paper focuses on the study and development on an automated face recognition system with the potential application for office door access control. The technique of eigenfaces based on the principle component analysis (PCA) and artificial neural networks have been applied into the system. The study includes the analysis of the influences of three main factors of face recognition namely illumination, distance and subject''s head orientation on the developed face recognition system purposely built for office door access control. The experimental results have shown that the developed system has achieved good performance of face recognition rate of 80% at the distance of camera and subject between 40 cm to 60 cm and the subject''s orientation head angle must be within the range of-20 to +20 degrees.
机译:当前,在公共或私人机构中,安全性已成为非常重要的问题,在该系统中,已经针对某些关键过程提出并开发了各种安全系统,例如人员身份识别,验证或识别(尤其是建筑物出入控制),警察的可疑身份识别,驾驶执照和很多其他的。自1980年代末以来,人脸识别一直是一个活跃的研究领域,具有众多应用,并且已成为安全系统开发中的重要元素之一。本文着重于自动人脸识别系统的研究与开发,该系统在办公门禁系统中具有潜在的应用前景。基于主成分分析(PCA)和人工神经网络的特征脸技术已被应用到系统中。该研究包括分析面部识别的三个主要因素,即照明,距离和对象的头部朝向,对专门为办公室门禁控制而开发的面部识别系统的影响。实验结果表明,所开发的系统在40 cm至60 cm的摄像头与被摄物体之间的距离上取得了80%的良好人脸识别率,并且被摄物体的方位头角必须在20度范围内到+20度。

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