Improved automatic age estimation algorithm using a hybrid feature selection
by Santhosh Kumar Gangadharaih; H.N. Suresh
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 12, No. 1, 2020

Abstract: Age estimation (AE) is one of the significant biometric behaviours for emphasising the identity authentication. In facial image, automatic-AE is an actively researched topic, which is also an important but challenging study in the field of face recognition. This paper explores several algorithms utilised to improve AE and the combination of features and classifiers are associated. Initially, the facial image databases are trained and then the features are extracted by employing several algorithms like histogram of oriented gradients (HOG), binary robust invariant scalable keypoints (BRISK), and local binary pattern (LBP). Here, the AE is done in three various age groups from 20 to 30, 31 to 50 and above 50. The age groups are classified by utilising Naïve Bayes classifier (NBC). AE model is calculated by employing the Indian face age database (IFAD) and labelled Wikipedia face (LWF) aging databases obtaining optimistic result with success rate.

Online publication date: Mon, 02-Dec-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Aided Engineering and Technology (IJCAET):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email