Face Recognition System Using Back Propagation Artificial Neural Networks

The problem in face recognition is to find the best match of an unknown image against a database of face models or to determine whether it does not match any of them well. In this method, we use back propagation neural network for implementation. It is an information processing system that has been developed as a generalization of the mathematical model of human recognition. The function of a neural network is to produce an output pattern when presented with an input pattern. The back propagation type of neural network is a feed forward system with training input pattern and weight adjustment with the associated error. The input neurons receive input signal and propagates into each hidden neuron, which again computes the activation to obtain the net output. This face recognition system is implemented using a MATLAB software package. In this we used the neural networks tool box in matlab. We found the transformation for different inputs and compared with unknown face that the given face is in database or not.