Open AccessFacial Recognition-Based Automatic Door Access System Using Extreme Learning Machine
Author(s) -
R F Rahmat,
Eleider Notarisman Zai,
Insidini Fawwaz,
Indra Aulia
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/851/1/012065
Subject(s) - computer science , artificial intelligence , biometrics , facial recognition system , face (sociological concept) , feature (linguistics) , pattern recognition (psychology) , three dimensional face recognition , artificial neural network , computer vision , local binary patterns , process (computing) , extreme learning machine , face detection , test data , image (mathematics) , social science , linguistics , philosophy , sociology , programming language , histogram , operating system
Facial recognition is one of the best forms of security since it is biometric-based security that uses biological features of the face. One of the artificial neural networks that can be implemented in the face recognition case is Extreme Learning Machine with the assistance of Local Binary Pattern in obtaining the facial features. The testing process in this study used 150 face images for training data and 60 face images for test data. The test was carried out using several three parameters of the hidden neuron numbers, namely 10, 30, and 50, and also five parameters of the image condition, namely feature, expression, face direction, lighting, and webcam distance. The system achieved the highest accuracy of 90% using 50 hidden neurons.