A REVIEW STUDY ON TWINS FACE IDENTIFICATION USING LBP TECHNIQUE

A user’s identify & emotional condition can be inferred a great deal from their face. Face recognition affects vital applications in numerous fields, including recognition for police departments, identification for banking and security system access, and identifying information, amongst many others. It is a fascinating and difficult topic. The three key components of our study project are face depiction, feature extraction, & classification. The subsequent methods for identification and recognition are determined by the face recognition, which represents how to model a face. In the feature extraction stage, the facial image’s most beneficial & distinctive traits are retrieved. The face image is compared to database pictures throughout the classification process. This paper concludes that the we empirically evaluate face recognition which considers both shape and texture information to represent face images based on Local Binary Patterns for person-independent face recognition. The face area is first divided into small regions from which Local Binary Patterns (LBP) are extracted and concatenated into a single feature vector. This feature vector forms an efficient representation of the face and is used to measure similarities between images.