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.
