An Improved Real-Time Face Recognition System at Low Resolution Based on Local Binary Pattern Histogram Algorithm and CLAHE

Local Binary Pattern based Resolution Variation Video-based Face Recognition

Video-based face recognition is a very challenging problem as there is a variation in resolution, illumination, pose, facial expressions and occlusion. In this paper, we have presented an approach for resolution variation video-based face recognition system using the combination of local binary pattern (LBP), principal component analysis (PCA) and feed forward neural network (FFNN). We used, st...

Multi-scale local Binary Pattern Histogram for Face Recognition

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...

Face Recognition using Local Ternary Pattern for Low Resolution Image

Face Recognition system is one of an effective system which is used for the identification of a person from a video frame or a digital image. The concept of FRS is primarily used in the field of security systems and hence can be get compared to other systems which are biometric in nature such as IRIS Recognition or Fingerprint systems. Apart from these techniques, Local Binary Patterns (LBP) al...

Face Identification Based on Contrast Limited Adaptive Histogram Equalization (CLAHE)

This paper proposes a face identification method based on Contrast Limited Adaptive Histogram Equalization (CLAHE) robust to facial expressions, occlusion and specially to illumination changes. Based on Eigenphases algorithm for feature extraction, the Principal Components Analysis (PCA) and the Phase Spectrum was used as feature extraction stage, and Support Vector Machine (SVM) as a classifie...