Facial Recognition using Modified Local Binary Pattern and Random Forest

Abstract

This paper presents an efficient algorithm for face recognition using the local binary pattern (LBP) and random forest (RF). The novelty of this research effort is that a modified local binary pattern (MLBP), which combines both the sign and magnitude features for the improvement of facial texture classification performance, is applied. Furthermore, RF is used to select the most important features from the extracted feature sequence. The performance of the proposed scheme is validated using a complex dataset, namely Craniofacial Longitudinal Morphological Face (MORPH) Album 1 dataset.