FACE RECOGNITION SYSTEM USING PRINCIPAL COMPONENT ANALYSIS AND BACK PROPAGATION NEURAL NETWORK

Abstract

Face recognition is a computer application which is used to indentify or verify a person in a digital image, based on digital image processing and is an active area of research. The face recognition system proves to be efficient in criminal identification, data privacy, home video surveillance systems etc. Various innovative face recognition systems have been developed so far using a wide range of algorithms. An efficient method of face recognition using Principal Component Analysis and Back Propagation Neural Network is presented in this work. In this work Principal Component Analysis (PCA) is used to extract the facial features and Back Propagation Neural Network is used for classifier to act the recognized image. This system is developed as mobile application. Face recognition on mobile phones are constantly improving and the majority is currently equipped with digital camera. This facilitates taking a large amount of photos everyday with a camera phone instead of a stand alone digital camera. The system can be trained the face images to become capable of automatically recognizing a person from the training face images. In this system, it has developed a human face recognition system using Principal Components Analysis (PCA) with Back Propagation Neural Network(BPNN). There are many techniques which have been used now for this purpose but here in this system our approach has concluded that principal components analysis with back propagation neural network worked even better than the individual Principal Components Analysis. Thus it has developed a face recognition system for human being using both above techniques.