An introduction to wavelets
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Discriminant Analysis of Principal Components for Face Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Locating and extracting the eye in human face images
Pattern Recognition
IEEE Transactions on Image Processing
An efficient illumination normalization method for face recognition
Pattern Recognition Letters
MutualBoost learning for selecting Gabor features for face recognition
Pattern Recognition Letters
Learning the best subset of local features for face recognition
Pattern Recognition
MutualBoost learning for selecting Gabor features for face recognition
Pattern Recognition Letters - Special issue on vision for crime detection and prevention
Elastic shape-texture matching for human face recognition
Pattern Recognition
Information theory for Gabor feature selection for face recognition
EURASIP Journal on Applied Signal Processing
A multi-matcher for ear authentication
Pattern Recognition Letters
Simplified Gabor wavelets for human face recognition
Pattern Recognition
A Biological Intelligent Access Control System Based on DSP and NIR Technology
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
On selecting Gabor features for biometric authentication
International Journal of Computer Applications in Technology
Face detection using simplified Gabor features and hierarchical regions in a cascade of classifiers
Pattern Recognition Letters
Complex wavelet transform-based face recognition
EURASIP Journal on Advances in Signal Processing
Automatic 3D face recognition from depth and intensity Gabor features
Pattern Recognition
Hierarchical ensemble of global and local classifiers for face recognition
IEEE Transactions on Image Processing
Image and Vision Computing
Image and Vision Computing
Illumination invariant face recognition
Pattern Recognition
Improved competitive code for palmprint recognition using simplified Gabor filter
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Facial affect recognition using regularized discriminant analysis-based algorithms
EURASIP Journal on Advances in Signal Processing - Special issue on video analysis for human behavior understanding
Ellipse Invariant Algorithm for Texture Classification
Fundamenta Informaticae
MLP-based face recognition with Gabor filters and PCA
Pattern Recognition and Image Analysis
Selective generation of Gabor features for fast face recognition on mobile devices
Pattern Recognition Letters
Multi-resolution feature fusion for face recognition
Pattern Recognition
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The Gabor feature is effective for facial image representation, while linear discriminant analysis (LDA) can extract the most discriminant information from the Gabor feature for face recognition. In practice, the dimension of a Gabor feature vector is so high that the computation and memory requirements are prohibitively large. To reduce the dimension, one simple scheme is to extract the Gabor feature at sub-sampled positions, usually in a regular grid, in a face region. However, this scheme is not effective enough and degrades the recognition performance. In this paper, we propose a method to determine the optimal position for extracting the Gabor feature such that the number of feature points is as small as possible while the representation capability of the points is as high as possible. The subsampled positions of the feature points are determined by a mask generated from a set of training images by means of principal component analysis (PCA). With the feature vector of reduced dimension, a subspace LDA is applied for face recognition, i.e., PCA is first used to reduce the dimension of the Gabor feature vectors generated from the subsampled positions, and then a common LDA is applied. Experimental results show that the new sampling method is simple, and effective for both dimension reduction and image representation. The recognition rate based on our proposed scheme is also higher than that achieved using a regular sampling method in a face region.