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Analysis of neural networks for face recognition systems with feature extraction to develop an eye localization based method

机译:具有特征提取的面部识别系统神经网络分析开发基于眼部化的方法

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This paper provides an analysis of Multilayer Perceptron Backpropagation neural networks (MLP/BP NN), Radial Basis Function neural networks (RBF NN), and Multilayer Cluster neural networks (MCNN) applications in face recognition. Feature extraction methods involved in the analysis are the Discrete Wavelet transform (DWT), Discrete Radon transform (DRT), Discrete Cosine transform (DCT) and the principal component analysis (PCA) technique. Algorithms were developed using Matlab and tested on the ORL database. Also, a new proposed 2-stage face recognition system is presented based on eye localization and a windowed face area for recognition.
机译:本文提供了对人物识别中的多层的感知BROPPRAGAGAGAGAGAGE神经网络(MLP / BP NN),径向基函数神经网络(RBF NN)和多层群集神经网络(MCNN)应用的分析。分析中涉及的特征提取方法是离散小波变换(DWT),离散氡变换(DRT),离散余弦变换(DCT)和主成分分析(PCA)技术。使用MATLAB开发算法并在ORL数据库上进行测试。此外,基于眼部定位和窗口面积的窗口面积来呈现新的提出的2级面部识别系统。

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