Face description with local binary patterns: application to face recognition.
This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a face descriptor. The performance of the proposed method is assessed in the face recognition problem under different challenges. Other applications and several extensions are also discussed.
Ahonen
Timo
T
Machine Vision Group, Department of Electrical Information Engineering, University of Oulu, Finland. tahonen@ee.oulu.fi
Hadid
Abdenour
A
Pietikäinen
Matti
M
D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods*; D005145:Face / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted