结合DCT、PCA和bp神经网络的人脸识别算法

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI:10.1109/ICACI.2012.6463254

Guoliang Yang, Linjia Xu

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引用次数: 1

摘要

本文提出了一种集成的人脸识别算法。采用离散余弦变换和主成分分析对人脸图像进行降维和特征提取，然后通过BP神经网络分类器对人脸图像进行训练和测试。并寻求其他方法如最近邻分类器与BP神经网络进行比较。仿真结果表明了该算法的有效性。

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Face recognition algorithm combined with DCT, PCA and BPNN

This paper provides an integrated algorithm to deal with face recognition. It uses discrete cosine transform and principal component analysis to reduce dimensions and extract face features, and then trains and tests face images through the BP neural network classifier. It also seeks for other method such as the nearest neighbor classifier to have a comparison with BP neural network. Simulation result shows the effectiveness of this algorithm.

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2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)

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