Face Recognition System using Deep Face and Neural Network

The process of face recognition involves the determination of facial features in an image, by recognizing those features and comparing them to one of the many faces in the database. There are many algorithms capable of performing face recognition; such as: PCA, Discrete Cosine Transform, 3D recognition methods, Gabor Wavelets method etc. There were many issues to consider when choosing a face recognition method. With these in mind the PCA based method of face recognition has found to be better because: Simplest and easiest method to implement, Very fast computation time. PCA has the ability to recognizing a face with a different background is difficult. In this research paper, the face recognition system proposed the Detection time, false negative in missed faces and optimality of the face. This proposed research work has been focused on optimality features of the neural network for the face images and detection time. In this paper, we have applied the neural network for three parameters such – detection time, false acceptance rate, successful rates, no. of failure, and cross correlation