Ring-to-line mapping and orientation invariant transform for Chinese seal character recognition
International Journal of Computer Mathematics
Information Sciences: an International Journal
Palm-print recognition by matrix discriminator
Expert Systems with Applications: An International Journal
Feature extraction based on Laplacian bidirectional maximum margin criterion
Pattern Recognition
Incremental learning of bidirectional principal components for face recognition
Pattern Recognition
Interval type-2 fuzzy logic and modular neural networks for face recognition applications
Applied Soft Computing
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
Color face recognition for degraded face images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A feature extraction method for use with bimodal biometrics
Pattern Recognition
r-Theta and orientation invariant transform and signal combining for fingerprint recognition
Expert Systems with Applications: An International Journal
Regularized locality preserving projections and its extensions for face recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Orientation distance-based discriminative feature extraction for multi-class classification
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Letters: Laplacian bidirectional PCA for face recognition
Neurocomputing
Block principal component analysis with L1-norm for image analysis
Pattern Recognition Letters
Probabilistic learning of similarity measures for tensor PCA
Pattern Recognition Letters
A feature construction method for general object recognition
Pattern Recognition
An efficient approach for face recognition based on common eigenvalues
Pattern Recognition
Hi-index | 0.00 |
Appearance-based methods, especially linear discriminant analysis (LDA), have been very successful in facial feature extraction, but the recognition performance of LDA is often degraded by the so-called "small sample size" (SSS) problem. One popular solution to the SSS problem is principal component analysis(PCA)+LDA (Fisherfaces), but the LDA in other low-dimensional subspaces may be more effective. In this correspondence, we proposed a novel fast feature extraction technique, bidirectional PCA (BDPCA) plus LDA (BDPCA+LDA), which performs an LDA in the BDPCA subspace. Two face databases, the ORL and the Facial Recognition Technology (FERET) databases, are used to evaluate BDPCA+LDA. Experimental results show that BDPCA+LDA needs less computational and memory requirements and has a higher recognition accuracy than PCA+LDA