Rotation and noise invariant near-infrared face recognition by means of Zernike moments and spectral regression discriminant analysis

@article{Farokhi2013RotationAN,
  title={Rotation and noise invariant near-infrared face recognition by means of Zernike moments and spectral regression discriminant analysis},
  author={Sajad Farokhi and Siti Mariyam Hj. Shamsuddin and Jan Flusser and Usman Ullah Sheikh and Mohammad Khansari and Kourosh Jafari-Khouzani},
  journal={Journal of Electronic Imaging},
  year={2013},
  volume={22}
}
Abstract. Face recognition is a rapidly growing research area, which is based heavily on the methods of machine learning, computer vision, and image processing. We propose a rotation and noise invariant near-infrared face-recognition system using an orthogonal invariant moment, namely, Zernike moments (ZMs) as a feature extractor in the near-infrared domain and spectral regression discriminant analysis (SRDA) as an efficient algorithm to decrease the computational complexity of the system… 
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