A hybrid approach for face recognition using LBP and multi level classifier Online publication date: Tue, 02-May-2023
by Mukesh Kumar Gupta; Pankaj Dadheech; Ankit Kumar; Ashok Kumar Saini; Neha Janu; Sanwta Ram Dogiwal
International Journal of Biometrics (IJBM), Vol. 15, No. 3/4, 2023
Abstract: General face recognition, a task performed by humans in daily activities, is derived from a virtually uncontrolled environment. This paper presents a facial recognition system based on random forest and support vector machine. When compared to previous methods, this approach achieves high accuracy. In this paper, we proposed a hybrid method using SVM and random forest classification. The RF+SVM method predicts rapid growth in popularity. This combined method aids in high recognition speed with a wide range of faces and emotions. We also compared the algorithm to previous techniques. Each experiment made use of a free internet database. In the experiment, 400 photographs of 40 people are used. The reason for the improved results in this paper's hybrid vehicle classification methodology is that it combines the advantages of both traditional SVM and RF class methods. The proposed system has an accuracy of 98.6%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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:
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
Our Blog 
Follow us on Twitter 
Visit us on Facebook