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首页> 外文期刊>International Journal of Scientific & Technology Research >Automatic Door Access System Using Face Recognition
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Automatic Door Access System Using Face Recognition

机译:使用人脸识别的自动门禁系统

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摘要

Abstract: Most doors are controlled by persons with the use of keys, security cards, password or pattern to open the door. Theaim of this paper is to help users forimprovement of the door security of sensitive locations by using face detection and recognition. Face is a complex multidimensional structure and needs good computing techniques for detection and recognition. This paper is comprised mainly of three subsystems: namely face detection, face recognition and automatic door access control. Face detection is the process of detecting the region of face in an image. The face is detected by using the viola jones method and face recognition is implemented by using the Principal Component Analysis (PCA). Face Recognition based on PCA is generally referred to as the use of Eigenfaces.If a face is recognized, it is known, else it is unknown. The door will open automatically for the known person due to the command of the microcontroller. On the other hand, alarm will ring for the unknown person. Since PCA reduces the dimensions of face images without losing important features, facial images for many persons can be stored in the database. Although many training images are used, computational efficiency cannot be decreased significantly. Therefore, face recognition using PCA can be more useful for door security system than other face recognition schemes.
机译:摘要:大多数门都是由人控制的,使用钥匙,安全卡,密码或图案来打开门。本文的目的是通过面部检测和识别来帮助用户提高敏感位置的门安全性。人脸是一个复杂的多维结构,需要良好的计算技术来进行检测和识别。本文主要由三个子系统组成:面部检测,面部识别和自动门禁控制。人脸检测是检测图像中人脸区域的过程。使用中提琴琼斯方法检测面部,并使用主成分分析(PCA)进行面部识别。基于PCA的人脸识别通常被称为特征脸的使用,如果识别出人脸,则已知该人脸,否则未知。由于微控制器的命令,门将自动为已知人员打开。另一方面,警报会为未知的人响起。由于PCA在不丢失重要特征的情况下减小了面部图像的尺寸,因此可以将许多人的面部图像存储在数据库中。尽管使用了许多训练图像,但是不能显着降低计算效率。因此,与其他人脸识别方案相比,使用PCA的人脸识别对门防盗系统更为有用。

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