Open AccessRealization and optimization of face recognition system based on MATLAB
Author(s) -
Yan Xiao,
Gaqiong Liu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032091
Subject(s) - facial recognition system , local binary patterns , matlab , eigenface , computer science , realization (probability) , shadow (psychology) , face (sociological concept) , artificial intelligence , compensation (psychology) , computer vision , pattern recognition (psychology) , binary number , three dimensional face recognition , face detection , image (mathematics) , mathematics , operating system , psychology , social science , statistics , sociology , psychoanalysis , psychotherapist , histogram , arithmetic
In this dissertation, several techniques used in face recognition have been investigated. Besides, a critical problem in face recognition which is illumination variation has been considered. In this dissertation, a face recognition system has been built using MATLAB. In this system, after the Eigenface has been achieved, two techniques to deal with illumination changing have been implemented, shadow compensation and local binary pattern (LBP) respectively. After the experiment, LBP shows a better performance than shadow compensation on Yale B cropped database.