Occlusion detection and recognizing human face using neural network

Abstract

Face recognition is one of the most important problems of verifying or identifying a face from query image or input image. This system has emerged as an important field in case of surveillance systems. Face detection is a very powerful tool for video surveillance, human computer interface, face recognition, and image database management. Occlusion means extraneous objects that hinder face recognition, e.g., face covered with scarf, wearing glasses, beard, cap etc., is one of the greatest challenges in face recognition systems. Other issues are illumination, pose, expressions etc. An efficient method is used for detection of occlusions, which specifies the missing information in the occluded face. Method used for face detection is Viola-Jones algorithm, for occlusion detection and reconstruction of face fast weighted PCA is used are Neural Network (NN) is used for face recognition. Other appropriate methods are Principal Component Analysis (PCA), Local Binary Pattern (LBP), Eigenfaces. Propose method which is used will detect occluded face and recognize the face with the help of given same faces from the database.