Fingerprint liveness detection using gradient-based texture features

Document Type

Article

Publication Date

2-1-2017

Abstract

Fingerprint-based recognition systems have been increasingly deployed in various applications nowadays. However, the recognition systems can be spoofed by using an accurate imitation of a live fingerprint such as an artificially made fingerprint. In this paper, we propose a novel software-based fingerprint liveness detection method which achieves good detection accuracy. We regard the fingerprint liveness detection as a two-class classification problem and construct co-occurrence array from image gradients to extract features. In doing so, the quantization operation is firstly conducted on the images. Then, the horizontal and vertical gradients at each pixel are calculated, and the gradients of large absolute values are truncated into a reduced range. Finally, the second-order and the third-order co-occurrence arrays are constructed from the truncated gradients, and the elements of the co-occurrence arrays are directly used as features. The second-order and the third-order co-occurrence array features are separately utilized to train support vector machine classifiers on two publicly available databases used in Fingerprint Liveness Detection Competition 2009 and 2011. The experimental results have demonstrated that the features extracted with the third-order co-occurrence array achieve better detection accuracy than that with the second-order co-occurrence array and outperform the state-of-the-art methods.

Identifier

84978924350 (Scopus)

Publication Title

Signal Image and Video Processing

External Full Text Location

https://doi.org/10.1007/s11760-016-0936-z

e-ISSN

18631711

ISSN

18631703

First Page

381

Last Page

388

Issue

2

Volume

11

Grant

U1536206

Fund Ref

National Natural Science Foundation of China

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