Fundamentals of digital image processing
Fundamentals of digital image processing
On Photometric Issues in 3D Visual Recognition from aSingle 2D Image
International Journal of Computer Vision
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
What is the set of images of an object under all possible lighting conditions?
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Pose-Invariant Face Recognition with Parametric Linear Subspaces
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Think globally, fit locally: unsupervised learning of low dimensional manifolds
The Journal of Machine Learning Research
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Acquiring Linear Subspaces for Face Recognition under Variable Lighting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose-Robust Face Recognition Using Geometry Assisted Probabilistic Modeling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Mastering Digital Photography, Second Edition (Mastering)
Mastering Digital Photography, Second Edition (Mastering)
Face recognition using discriminant eigenvectors
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
Two-dimensional Laplacianfaces method for face recognition
Pattern Recognition
Towards a theoretical foundation for Laplacian-based manifold methods
Journal of Computer and System Sciences
Video-based face recognition using adaptive hidden markov models
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
Face Recognition Using an Enhanced Independent Component Analysis Approach
IEEE Transactions on Neural Networks
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We present an enhanced principal component analysis (PCA) algorithm for improving rate of face recognition. The proposed pre-processing method, termed as perfect histogram matching, modifies the image histogram to match a Gaussian shaped tonal distribution in the face images such that spatially the entire set of face images presents similar facial gray-level intensities while the face content in the frequency domain remains mostly unaltered. Computationally inexpensive, the perfect histogram matching algorithm proves to yield superior results when applied as a pre-processing module prior to the conventional PCA algorithm for face recognition. Experimental results are presented to demonstrate effectiveness of the technique.