Digital image processing
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
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
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Description of interest regions with local binary patterns
Pattern Recognition
IEEE Transactions on Image Processing
Enhanced local texture feature sets for face recognition under difficult lighting conditions
IEEE Transactions on Image Processing
Multi-resolution histograms of local variation patterns (MHLVP) for robust face recognition
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Image Processing
Gabor-Based Region Covariance Matrices for Face Recognition
IEEE Transactions on Circuits and Systems for Video Technology
The CSU Face Identification Evaluation System
Machine Vision and Applications
Hi-index | 0.00 |
In recent years, local feature descriptors have received more and more attention due to their effectiveness in the field of face recognition. Local Derivative Patterns (LDPs) for local feature descriptions attract researchers' great interest. However, an LDP produces 2p different patterns for p neighbors through the transition of LDPs for an image, which lead to high dimension features for image analysis. In this paper, LDPs are expanded to Uniform Local Derivative Patterns (ULDPs) that have the same binary encoding way as LDPs but different transition patterns by introducing uniform patterns. A uniform pattern is the one that contains at most two bitwise transitions from 0 to 1 or vice versa when the binary bit is circular. Then, the number of the transition patterns is reduced from 2p to p(p驴1)+3 for p neighbors, e.g., 256 to 59 for p驴=驴8. For face recognition, the histogram features are combined together in four directions, and both non-preprocessed and preprocessed images are used to evaluate the performance of the proposed ULDPs method. Extensive experimental results on three publicly available face databases show that the proposed ULDPs approach has better recognition performance than that obtained by using the LDPs method.