Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4581
Title: Investigating Fingerprint Quality Features for Liveness Detection
Authors: Anshul, Ashutosh
Jha, Ashwini
Dey, Somnath
Keywords: Feature extraction;Quality control;Automatic fingerprint identification systems;Fake fingerprints;Fingerprint images;Fingerprint liveness detection;Fingerprint qualities;Liveness detection;Quality features;Recognition systems;Palmprint recognition
Issue Date: 2020
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Sharma, R. P., Anshul, A., Jha, A., & Dey, S. (2020). Investigating fingerprint quality features for liveness detection doi:10.1007/978-3-030-66187-8_28
Abstract: Fingerprint-based recognition systems are vulnerable to presentation attacks. To identify these attacks one of the solution is fingerprint liveness detection which ensures the presence of a live or fake fingerprint. In this paper, we have investigated the use of quality features for the detection of liveness of given fingerprint image. We have proposed a novel set of features which can be used for liveness detection in fingerprint images. Along with these features, efficacy of other existing quality features is also evaluated for the liveness detection. Based on these quality features fingerprint images are classified into fake and live fingerprints using various classifiers. The robustness of the proposed approach is evaluated on publicly available LivDet 2015 competition database. The advantage of the proposed method is that it utilizes the quality features for liveness detection which are also utilized for the quality analysis of fingerprint images. Therefore, it is possible to combine two different modules, namely, quality analysis and liveness detection of the Automatic Fingerprint Identification System (AFIS) using our proposed approach. © 2020, Springer Nature Switzerland AG.
URI: https://doi.org/10.1007/978-3-030-66187-8_28
https://dspace.iiti.ac.in/handle/123456789/4581
ISBN: 9783030661861
ISSN: 0302-9743
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: