摘要
本文提出小波分析与主成分分析在人脸识别方面的应用,介绍了小波分析和主成分分析在ORL人脸中的特征提取,介绍了RBF神经网络算法的原理和在本文中的应用,利用RBF神经网络来实现人脸识别率判断,对小波分析层数以及RBF扩散率进行了研究。最终确定识别率最高的小波分析层数,下一步准备将人脸图像识别应用于医院实际环境中。
This paper presents the application of wavelet analysis and principal component analysis in face recognition,and introduces the feature extraction of wavelet analysis and principal component analysis in ORL face recognition.After that,this paper introduces the principle of RBF neural network algorithm and its application in this research,and uses RBF neural network to judge the face recognition rate.Accordingly,the paper studies the number of wavelet analysis layers and RBF diffusion rate.Finally,the wavelet analysis layer with the highest recognition rate is determined,and the face recognition could be applied to the actual environment of hospitals in the next step.
作者
吴冠朋
WU Guanpeng(Shandong Provincial Third Hospital,Jinan 250031,China)
出处
《智能计算机与应用》
2023年第3期198-201,共4页
Intelligent Computer and Applications
关键词
小波分析
主成分分析
特征提取
径向基神经网络
wavelet analysis
principal component analysis
feature extraction
radial basis function neural network
作者简介
吴冠朋(1989-),男,信息网络部工程师,主要研究方向:人工智能、图像处理技术。
