Open AccessANN Classifier for Human Age Classification
Author(s) -
Thanuja R*,
Dr.A.Umama keswari,
Rubidha Devi D
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.c5430.098319
Subject(s) - leaps , artificial intelligence , biometrics , computer science , local binary patterns , classifier (uml) , face (sociological concept) , pattern recognition (psychology) , facial recognition system , wrinkle , artificial neural network , machine learning , computer vision , image (mathematics) , social science , sociology , financial economics , economics , histogram , materials science , composite material
Face recognition is an interesting research study with many researchers from computer vision and biometrics fields.The performance of existing methods on real-world images is still significantly lacking, especially when compared to the tremendous leaps in performance recently reported for the related task of face recognition. In this paper we propose a novel technique to group the age of a human dependent on facial skin maturing highlights. Artificial Neural Network (ANN) is proposed to characterize human age into different age gatherings. The ideal highlights are removed utilizing advanced picture handling methods like Local Binary Pattern (LBP), Elliptical Local Binary Pattern (ELBP) and Wrinkle Analysis. The proposed age characterization structure is prepared to test with human face pictures from SQL database with high precision.