Parallel structure system employing PCA and VQ in the transform domain for facial recognition

M. Abdelwahab, W. Mikhael
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Abstract

Recently, due to emerging critical applications such as biomedical, and security applications, the area of intelligent signal processing has been receiving considerable attention. In this contribution, we present an intelligent signal processing system applied to signal recognition and classification. The system employs different structures, multicriteria and multitransform techniques. In addition, principal component analysis in the transform domain in conjunction with vector quantization is developed which result in further improvement in the recognition accuracy and dimensionality reduction. Experimental results are given which confirm the excellent properties of the proposed approaches.
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在变换域采用PCA和VQ的并行结构系统进行人脸识别
近年来,由于新兴的关键应用,如生物医学和安全应用,智能信号处理领域受到了相当大的关注。在这篇文章中,我们提出了一个应用于信号识别和分类的智能信号处理系统。该系统采用了不同的结构、多准则和多变换技术。此外,将变换域的主成分分析与矢量量化相结合,进一步提高了识别精度和降维效果。实验结果证实了所提方法的优良性能。
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