Open AccessExtended Local Binary Pattern Features based Face Recognition using Multilevel SVM Classifier
Author(s) -
S Sujay,
H S Manjunatha Reddy
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c5481.098319
Subject(s) - artificial intelligence , pattern recognition (psychology) , local binary patterns , computer science , biometrics , histogram , facial recognition system , support vector machine , classifier (uml) , face (sociological concept) , feature extraction , computer vision , image (mathematics) , social science , sociology
The Face recognition method is one of the authoritative biometric system in recognition methods to recognize the individual, because face is a distinctive biometric trait of an human being and it is the superior method of recognition. This paper proposes a novel Face recognition method by using extended LBP features. The pre-processing is carried out to extract the face area using viola-johns algorithm and all images are resized to 100x100. The LBP operator is applied on resized face images by rotating the each image by 15 degrees, i.e., at 7 degree left and 7 degree right and at zero degree to extract the feature vectors and final features are obtained by applying histogram technique. The SVM classifier is used for matching the database images with test images to measure the performance such as TSR, FAR, FRR & EER. The performance parameters are compared with existing algorithms for YALE and FERET database.