Multi-Orientation Log-Gabor Local Binary Pattern for Face Representation and Recognition

Face Recognition Using Gabor Volume Based Local Binary Pattern

The image space, scale and orientation domains can give valuable clues not seen in either individual of the domains. First we decomposed the face image into different orientation and scale by Gabor filter. Second, we combine local binary pattern analysis with Gabor. It gives a good face representation for recognition. Then we classify in discriminant based up on median histogram distance. The f...

Multi-scale local Binary Pattern Histogram for Face Recognition

Weighted Multi-scale Local Binary Pattern Histograms for Face Recognition

This paper proposes a novel face recognition methodology, which is based on the combination of the texture operator, namely Multi-scale Local Binary Pattern (MSLBP), face image filtering and discriminative feature weighting algorithms. Presented MSLBP principle enhances the discriminative power of the original Local Binary Pattern operator. The combination of the MSLBP and low-pass filtering im...

Modelling of Eyeball with Pan/Tilt Mechanism and Intelligent Face Recognition Using Local Binary Pattern Operator

This paper describes the vision system for a humanoid robot, which includes the mechanism that controls eyeball orientation and blinking process. Along with the mechanism designed, the orientation of the camera, integrated with controlling servomotors. This vision system is a bio-mimic, which is  designed to match the size of human eye. This prototype runs face recognition and identifies, match...

Learned local Gabor patterns for face representation and recognition

In this paper, we propose Learned Local Gabor Patterns (LLGP) for face representation and recognition. The proposed method is based on Gabor feature and the concept of texton, and defines the feature cliques which appear frequently in Gabor features as the basic patterns. Different from Local Binary Patterns (LBP) whose patterns are predefined, the local patterns in our approach are learned fro...