Face Recognition Based On Local Binary Pattern

Abstract

Facial analysis has been an important research field due its wide range of applications like: law enforcement, surveillance, entertainment like video games and virtual reality, information security, banking, human computer interface, etc. The original interest in facial analysis relied on face recognition, but later on the interest in the field was extended and research efforts where focused in the appearance of model-based image, video coding, face tracking, pose estimation, facial expression, emotion analysis and video indexing. Face detection and recognition are still a very difficult challenge and there is no unique method that provides an efficient solution to all situations face processing may encounter. In this paper a novel approach is presented to face recognition which considers both shape and texture information to represent the face. The face area is first divided into small regions from which Local Binary Pattern (LBP) histograms are extracted and concatenated into a single, spatially enhanced feature histogram efficiently representing the face image. Extensive experimental research proves the superiority of the proposed method in respect of its simplicity and efficiency in very fast feature extraction.