The design of 2-D nonseparable directional perfect reconstruction filter banks
Multidimensional Systems and Signal Processing
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rapid and brief communication: Face recognition based on 2D Fisherface approach
Pattern Recognition
Adaptive quasiconformal kernel discriminant analysis
Neurocomputing
Neural Computing and Applications
Kernel optimization-based discriminant analysis for face recognition
Neural Computing and Applications
Chaos and NDFT-based spread spectrum concealing of fingerprint-biometric data into audio signals
Digital Signal Processing
Performance evaluation of score level fusion in multimodal biometric systems
Pattern Recognition
A filter bank for the directional decomposition of images: theoryand design
IEEE Transactions on Signal Processing
On image matrix based feature extraction algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improved structures of maximally decimated directional filter Banks for spatial image analysis
IEEE Transactions on Image Processing
Editorial: High performance biometrics recognition algorithms and systems
Future Generation Computer Systems
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A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results confirm that the recognition rate of the proposed system is higher than the other popular algorithms.