Open AccessCombined features for face recognition under illumination variation
Author(s) -
Choi SangIl
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2015.2936
Subject(s) - pattern recognition (psychology) , artificial intelligence , facial recognition system , discriminant , linear discriminant analysis , face (sociological concept) , computer science , variation (astronomy) , set (abstract data type) , feature extraction , three dimensional face recognition , computer vision , face detection , social science , physics , sociology , astrophysics , programming language
A robust face recognition method that utilises a set of combined features is proposed to effectively conduct face recognition with images taken under diverse illumination variations. This method extracts discriminant features from different methods, both of which have different characteristics. To exploit the respective advantage of each method, the respective discriminability of the features extracted by each method is measured based on the discriminant distance criterion of each method. The experimental results show that the proposed features result in improved recognition performance under illumination variation.