A comprehensive age estimation on face images using hybrid filter based feature extraction

Abstract

Biometric based security applications are drastically growing and it is more essential in various emerging fields such as military, surveillance systems, crime, VISA processing systems etc. One of the human-computer-interaction fields is designing an intelligent application for estimating the age automatically using face images. The main objective is to estimate the human age using facial features and to improve its accuracy. In order to improve the age estimation accuracy, the wrinkles and end point of the wrinkles on the face image are considered. To estimate the age, first the orientation features of face image are extracted using Gabor filter; second the local wrinkle features known as minutiae are extracted using m × m wrinkle patterns on the face image by a hybrid filter. The minutiae points provide accurate information on the frequencies of the facial features. The effectiveness of the proposed approach is experimented on the publicly available FG-NET and MORPH age databases and results are compared with the other existing methods. The obtained results proved that the proposed approach is better than the other approaches in terms of age estimation accuracy.