基于PCA算法的人脸识别自动开门系统

Phan Nhu Quan, Phan Nhu Phuong, Pham Van Toan, Nguyen Duc Tien, Sowmyanarayanan Murugan
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引用次数: 0

摘要

提出了一种应用主成分分析(PCA)算法对自动开门系统进行人脸识别的解决方案。在本研究中,主要使用PCA算法来识别图像对象,使用协方差矩阵的特征向量形成的特征向量来将图像数据从原始轴重新定向到主成分,用于识别主成分。图像数据集由20张照片组成。利用UART (Universal Asynchronous Receiver Transmitter)通信将信号传输到Arduino微控制器,控制伺服电机运行开门。仿真结果表明,该方法精度高,处理速度快。
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Automatic Door Opening System Using Face Recognition with PCA Algorithm
This paper presents a solution to the automatic door opening system by face recognition by applying PCA (Principal Component Analysis) algorithm. In this work, the PCA algorithm is primarily used to recognize image objects, the feature vector formed using the eigenvectors of the covariance matrix to reorient the image data from the original axes to the ones is used to identify the principal components. The image dataset consists of twenty photos. Using UART (Universal Asynchronous Receiver Transmitter) communication to transmit signal to the Arduino microcontroller to control the servo motor run to open the door. The simulation results show that the proposed solution gives high accuracy and the processing speed is quite fast.
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