The implementation of the visitor access control system for the senior citizen based on the LBP face recognition

Jia-Jing Lin, Shih-Chang Huang
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引用次数: 10

Abstract

Many admission control systems require the face recognition processing in real time to guarantee the security. There are many well-known face recognition technologies have been proposed such as the linear discriminant analysis (LDA), discrete cosine transform (DCT), principal component analysis (PCA), and local binary pattern (LBP). In this study, we implemented an LBP-based visitor access control system for the senior citizen. The embedded platform to install the LBP is Raspberry Pi. The OpenCV is adapted as the classifier and the USB camera is used as the input device for capturing the face images. The Eigenvectors of the images in the training set are compared with the input face image for identify a person. The experimental results show that the implemented system can achieve 90% face recognition rate. The implemented system is low-cost and suitable for developing the visitor access control system for the senior citizen.
基于LBP人脸识别的老年人访客门禁系统的实现
许多入场控制系统需要实时进行人脸识别处理,以保证安全性。近年来,人们提出了许多著名的人脸识别技术,如线性判别分析(LDA)、离散余弦变换(DCT)、主成分分析(PCA)和局部二值模式(LBP)等。在这项研究中,我们实现了一个基于lbp的老年人访客访问控制系统。安装LBP的嵌入式平台为Raspberry Pi。采用OpenCV作为分类器,使用USB摄像头作为采集人脸图像的输入设备。将训练集中图像的特征向量与输入的人脸图像进行比较,用于识别人脸。实验结果表明,所实现的系统可以达到90%的人脸识别率。所实现的系统成本低,适合开发老年人访客门禁系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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