Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-dimensional Laplacianfaces method for face recognition
Pattern Recognition
Feature extraction based on Laplacian bidirectional maximum margin criterion
Pattern Recognition
Two-dimensional discriminant locality preserving projections for face recognition
Pattern Recognition Letters
Two-dimensional maximum margin feature extraction for face recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
A novel discriminant analysis approach using angular fourier transform for face recognition
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Feature extraction based on fuzzy 2DLDA
Neurocomputing
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ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Face recognition via two dimensional locality preserving projection in frequency domain
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
Facial images dimensionality reduction and recognition by means of 2DKLT
Machine Graphics & Vision International Journal
Matrix pattern based minimum within-class scatter support vector machines
Applied Soft Computing
Face recognition using two-dimensional CCA and PLS
International Journal of Biometrics
Fast Kernel Discriminant Analysis for Classification of Liver Cancer Mass Spectra
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Two dimensional laplacianfaces method for face recognition
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Pattern Recognition Letters
A Fishervoice-SVM language identification system
PROPOR'12 Proceedings of the 10th international conference on Computational Processing of the Portuguese Language
Future Generation Computer Systems
Equivalence Between LDA/QR and Direct LDA
International Journal of Cognitive Informatics and Natural Intelligence
On approaching 2D-FPCA technique to improve image representation in frequency domain
Proceedings of the Fourth Symposium on Information and Communication Technology
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Two-dimensional (2D) discrimination analysis using methods such as 2D PCA and Image LDA is of interest in face recognition because it extracts discriminative features faster than one-dimensional (1D) discrimination analysis. However, existing 2D methods generally use more discriminative features and take longer to test than 1D methods. 2D PCA in particular cannot make full use of the Fisher discriminant criterion. Image LDA also has drawbacks in that it cannot perform 2D principal component analysis and discards components with poor discriminative capabilities. In addition, existing 2D methods cannot provide an automatic strategy to choose 2D principal components or discriminant vectors. In this paper, we propose 2D Fisherface, a novel discrimination approach that combines the two-stage ''PCA+LDA'' strategy and 2D discrimination techniques. It can extract face discriminative features by automatically selecting two-dimensional principal components and discriminant vectors. Using the AR database as the test data, it is shown that the proposed approach is faster and more effective than several representative 1D and 2D discrimination methods.