Intelligent System For Human Age Estimation Using Hybrid Machine Learning Technique

Abstract

 Nowadays, constructing automatic system for human age estimation is an interesting area for researchers asit covers a wide range of life activities such as authentication and identification,and many other lifetime aspects. Human face is the best part of body that estimates the age of a person based on the shape and appearance of a female or a male. Thediverse face characteristics ofpeople and agingdifferencestill provide several unique featureswhich encourageresearchers to deal with it.This researchproposed a robust system for age estimation based on hybrid machine learning techniques.The human faceimage is preprocessed firstly to keep the valuable information only within the system and discard the other.Feature extraction will be applied to images using LDA algorithm and the human face imagesare grouped into three age classes depending on the number of features extracted from each image. Then, the output imageswill be optimized using hybrid feature optimization technique adopting two inspired algorithms, firefly and Harmonyalgorithms.Theobtained features are classified using J48 classification algorithm.The achieved results showed that the proposed system performed precision of 91.3% and MAE by 1.06.