Open AccessDiscriminative local difference patterns for robust face recognition
Author(s) -
Chen Si,
Yan Yan
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2015.2802
Subject(s) - discriminative model , pattern recognition (psychology) , artificial intelligence , robustness (evolution) , linear discriminant analysis , facial recognition system , dimensionality reduction , computer science , feature extraction , face (sociological concept) , facial expression , curse of dimensionality , mathematics , computer vision , social science , biochemistry , gene , chemistry , sociology
A novel facial feature descriptor, termed discriminative local difference patterns (DLDP), is proposed for robust face recognition. DLDP extracts local difference patterns (LDP) based on directional texture operators. To improve the compactness and discriminability of LDP, a two‐stage linear discriminant analysis for dimensionality reduction is further applied. The proposed DLDP effectively captures the local and holistic characteristics of the face image and shows great tolerance to illumination changes, robustness to variations in pose and facial expression, and computational efficiency. Experimental results on challenging face databases show that DLDP consistently outperforms current state‐of‐the‐art facial feature descriptors.