Face recognition with Linear Discriminant Analysis and neural networks

Sepide Fatahi, Ehsan Zadkhosh, Abdollah Chalechale
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引用次数: 3

Abstract

In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available. The proposed method was tested on ORL face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.
基于线性判别分析和神经网络的人脸识别
提出了一种基于主成分分析(PCA)、线性判别分析(LDA)和神经网络的人脸识别方法。将PCA与LDA相结合,提高了LDA在少量图像样本情况下的性能。在ORL人脸数据库上进行了测试。在该数据库上的实验结果表明,与以往的方法相比,该方法在人脸识别方面具有较好的有效性。
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