Research on facial feature-based gender intelligent recognition based on the Adaboost algorithm
by Jing Wang
International Journal of Biometrics (IJBM), Vol. 13, No. 1, 2021

Abstract: In order to overcome the problem of poor facial recognition intelligence and weak gender judgment, a new method based on Adaboost algorithm for facial feature-based gender intelligence recognition is proposed in this paper. In this method, the three-dimensional special point detection, weak perspective projection, spatial region segmentation and other methods are employed to construct the facial feature information sampling model. The Adaboost algorithm is used to analyse the matching between facial features and gender, on which facial-feature gender intelligent recognition is performed according to the distribution of the eyes, nose and mouth of the face image, and the edge contour detection model of the face image is constructed. The experimental results show that the method has the advantages of good intelligence, high recognition precision and short time cost in face-based gender recognition.

Online publication date: Tue, 05-Jan-2021

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 Biometrics (IJBM):
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 subs@inderscience.com