Open AccessDEVELOPMENT OF BIOMETRIC METHODS AND INFORMATION SECURITY TOOLS
Author(s) -
Talgat Mazakov,
D. N. Narynbekovna
Publication year - 2021
Publication title -
izvestiâ nacionalʹnoj akademii nauk respubliki kazahstan. seriâ fiziko-matematičeskaâ/izvestiâ nacionalʹnoj akademii nauk respubliki kazahstan. seriâ fiziko-matematičeskaâ
Language(s) - English
Resource type - Journals
eISSN - 2518-1726
pISSN - 1991-346X
DOI - 10.32014/2021.2518-1726.30
Subject(s) - computer science , artificial neural network , facial recognition system , artificial intelligence , biometrics , backpropagation , face (sociological concept) , pattern recognition (psychology) , principal component analysis , toolbox , time delay neural network , matlab , feature extraction , identification (biology) , machine learning , data mining , botany , biology , social science , sociology , programming language , operating system
Now a day’s security is a big issue, the whole world has been working on the face recognition techniques as face is used for the extraction of facial features. An analysis has been done of the commonly used face recognition techniques. This paper presents a system for the recognition of face for identification and verification purposes by using Principal Component Analysis (PCA) with Back Propagation Neural Networks (BPNN) and the implementation of face recognition system is done by using neural network. The use of neural network is to produce an output pattern from input pattern. This system for facial recognition is implemented in MATLAB using neural networks toolbox. Back propagation Neural Network is multi-layered network in which weights are fixed but adjustment of weights can be done on the basis of sigmoidal function. This algorithm is a learning algorithm to train input and output data set. It also calculates how the error changes when weights are increased or decreased. This paper consists of background and future perspective of face recognition techniques and how these techniques can be improved.