期刊
NEURAL COMPUTING & APPLICATIONS
卷 24, 期 6, 页码 1317-1326出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-013-1356-4
关键词
Human face recognition; Ensemble of polyharmonic extreme learning machine; Fast discrete curvelet transform; 2-Dimension principal component analysis
资金
- National Nature Science Foundation of China [61101240, 61272023]
- Zhejiang Provincial Natural Science Foundation of China [Y6110117]
- Science Foundation of Zhejiang Education Office [Y201122002]
This paper proposes a classifier named ensemble of polyharmonic extreme learning machine, whose part weights are randomly assigned, and it is harmonic between the feedforward neural network and polynomial. The proposed classifier provides a method for human face recognition integrating fast discrete curvelet transform (FDCT) with 2-dimension principal component analysis (2DPCA). FDCT is taken to be a feature extractor to obtain facial features, and then these features are dimensionality reduced by 2DPCA to decrease the computational complexity before they are input to the classifier. Comparison experiments of the proposed method with some other state-of-the-art approaches for human face recognition have been carried out on five well-known face databases, and the experimental results show that the proposed method can achieve higher recognition rate.
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