Automated Age Prediction using Wrinkles Features of Facial Images and Neural Network

Automated age estimation is an important processing task that serves many purposes such as surveillance monitoring, marketing of products, authentication systems, find out the fugitive or missing person and security control etc. Therefore, estimating age from still face images by using facial features is trending research topic from past few years. An automated age group prediction system using wrinkle features of facial images and neural network is proposed in this paper. Three age groups including child, young, and old, are considered in the classification system. The prediction process is divided into three phases: image accumulation from different website, wrinkles feature extraction using image processing technique, and age classification using Neural Network. Different facial images of different age groups are collected from several websites. The wrinkles features are extracted from each image using image processing techniques and make a corresponding database. Finally, an Artificial Neural Network (ANN) is constructed for classification of new images which will use the wrinkle features as inputs to classify the image into one of three age groups. Using this process, we can predict the age group of a face of a person with satisfactory accuracy.