Detecting liveness of fingerprint biometrics Online publication date: Wed, 04-Jan-2017
by G. Arunalatha; M. Ezhilarasan
International Journal of Internet Protocol Technology (IJIPT), Vol. 9, No. 4, 2016
Abstract: Biometrics refer to automated recognition of individuals based on their biological and behavioral characteristics. Biometric systems are widely used for security. But biometric systems are vulnerable to a certain type of attack. The type 1 attack or direct attack is done at the sensor level using fake input. Spoofing refers to the fraudulent action by an unauthorised person into biometric systems using fake input that reproduces one of the authorised person's biometric inputs. Liveness detection provides an extra level of authentication to biometrics. The fingerprint liveness detection is performed by measuring the following features of the fingerprint. They are Gabor-Shen feature, orientation flow feature, and frequency domain feature. This approach is based on fingerprint image quality. The SVM classifier is used for classification. The ATVS database is used for conducting experiments. This technique is software based as it requires no external hardware. This approach is inexpensive.
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 Internet Protocol Technology (IJIPT):
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