Pose, illumination and expression invariant face recognition using laplacian of Gaussian and Local Binary Pattern

This paper presents an effective approach for the application of Face Recognition using Local Binary Pattern operator. The face image is firstly divided in to the sub regions to generate the locally enhanced Local Binary Histogram, which provide the features information on pixel level by creating LBP labels for histogram. Global Local Binary Histogram for the entire face image is obtained by concatenating all the individual local histograms. As a pre-processing technique the differential excitation of pixel is used to make the algorithm invariant to the illumination changes. The performance of the algorithm is verified under constrains like pose, illumination and expression variation.