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

  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},
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… 
Evaluating Feature Extractors and Dimension Reduction Methods for Near Infrared Face Recognition Systems
Experiments indicate that ZMs as a global feature extractor, UDWT as a local feature Extractor and SRDA as a dimension reduction method have superior overall performance compared to some other methods in the presence of facial expressions, eyeglasses, head rotation, image noise and misalignments.
Face Recognition Using Exact Gaussian-Hermit Moments
In this chapter, a new method is proposed for a highly accurate face recognition system where exact Gaussian-Hermit moments are used to extract the features of face images where the higher order EGHMs are able to capture the higher-order nonlinear features of these images.
Near Infrared Face Recognition: A Comparison of Moment-Based Approaches
Experiments conducted on CASIA NIR database showed that Zernike moments outperformed other moment-based methods for facial images with different challenges such as facial expressions, head pose and noise.
Color face recognition using novel fractional-order multi-channel exponent moments
This paper presents a novel color face recognition method that depends on a new family of fractional-order orthogonal functions, which is called Orthogonal fractional -order exponent functions, called FrMEMs, which are defined in polar coordinates over the unit circle and have many characteristics.
Expression, pose, and illumination invariant face recognition using lower order pseudo Zernike moments
A novel expression and pose invariant feature descriptor is presented by combining Daubechies discrete wavelets transform and lower order pseudo Zernike moments to obtain illumination invariance.
Bionic RSTN invariant feature extraction method for image recognition and its application
Several experimental results demonstrate that RSTN-invariant features have striking robustness, and capable to classify R STN images, and are practiced in traffic sign recognition.
Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis
A robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA) is proposed, which shows the high performance of the proposed scheme in comparison with state-of-the-art methods.


Higher order orthogonal moments for invariant facial expression recognition
An efficient method for human face recognition using wavelet transform and Zernike moments
  • H. Neo, Y. Pang, A. Teoh, D. Ngo
  • Computer Science
    Proceedings. International Conference on Computer Graphics, Imaging and Visualization, 2004. CGIV 2004.
  • 2004
The simulation results on Essex database indicates that higher order degree of WT combine with ZM achieve better performance with respect to recognition rate rather than using WT or ZM alone.
Highly Accurate and Fast Face Recognition Using Near Infrared Images
A novel design of camera hardware, and a learning based procedure for effective face and eye detection and recognition with the resulting imagery, which has demonstrated excellent accuracy, speed and usability.
Illumination Invariant Face Recognition Using Near-Infrared Images
An active near infrared (NIR) imaging system is presented that is able to produce face images of good condition regardless of visible lights in the environment, and it is shown that the resulting face images encode intrinsic information of the face, subject only to a monotonic transform in the gray tone.
Near infrared face recognition based on wavelet transform and 2DPCA
The experimental results based on near-infrared face database clearly showed that the proposed algorithm could get higher recognition rate than the traditional PCA and 2DPCA algorithm, which demonstrated the efficiency of the proposed method.
Wavelets and Face Recognition
An overview of wavelet, multiresolution representation and wavelet packet for their use in face recognition technology is given.
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.