This paper is published in Volume-3, Issue-6, 2017
Area
Image Processing and Security
Author
Vinu Thadevus Williams, Dr. K. S. Angel Viji
Org/Univ
College of Engineering Kidangoor, Kottayam, Kerala, India
Pub. Date
22 December, 2017
Paper ID
V3I6-1443
Publisher
Keywords
Finger Print Liveness, Low Level Features, Gabor Filters, SURF, PHOG, SVM, Random Forest, PCA

Citationsacebook

IEEE
Vinu Thadevus Williams, Dr. K. S. Angel Viji. Using Low Level Features -Fingerprint Liveness Detection from Single Image, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Vinu Thadevus Williams, Dr. K. S. Angel Viji (2017). Using Low Level Features -Fingerprint Liveness Detection from Single Image. International Journal of Advance Research, Ideas and Innovations in Technology, 3(6) www.IJARIIT.com.

MLA
Vinu Thadevus Williams, Dr. K. S. Angel Viji. "Using Low Level Features -Fingerprint Liveness Detection from Single Image." International Journal of Advance Research, Ideas and Innovations in Technology 3.6 (2017). www.IJARIIT.com.

Abstract

Fingerprint-based authentication systems have developed rapidly in the recent years. However, current fingerprint-based biometric systems are vulnerable to spoofing attacks. Moreover, the single feature-based static approach does not perform equally over different fingerprint sensors and spoofing materials. In this paper, propose a static software approach. Propose to combine low-level gradient features from speeded-up robust features, pyramid extension of the histograms of oriented gradient and texture features from Gabor wavelet using dynamic score level integration. Extract these features from a single fingerprint image to overcome the issues faced in dynamic software approaches, which require user cooperation and longer computational time.