Experimental results on palmvein-based personal recognition by multi-snapshot fusion of textural features
by Mohanad Abukmeil; Gian Luca Marcialis
International Journal of Biometrics (IJBM), Vol. 14, No. 1, 2022

Abstract: In this paper, we investigate multiple snapshot fusion of textural features for palmvein recognition including identification and verification. Although the literature proposed several approaches for palmvein recognition, the palmvein performance is still affected by identification and verification errors. As well-known, palmveins are usually described by line-based methods which enhance the vein flow. This is claimed to be unique from person to person. However, palmvein images are also characterised by texture that can be pointed out by textural features, which relies on recent and efficient hand crafted algorithms such as local binary patterns, local phase quantisation, local tera pattern, local directional pattern, and binarised statistical image features (LBP, LPQ, LTP, LDP and BSIF, respectively), among others. Finally, they can be easily managed at feature-level fusion, when more than one sample can be acquired for recognition. Therefore, multi-snapshot fusion can be adopted for exploiting these features complementarity. Our goal is to show that this is confirmed for palmvein recognition, thus allowing to achieve very high recognition rates on a well-known benchmark dataset.

Online publication date: Thu, 09-Dec-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