Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/55502
Title: A framework for liveness detection for direct attacks in the visible spectrum for multimodal ocular biometrics
Authors: Das, A.
Pal, U.
Ferrer, Miguel Angel 
Blumenstein, M.
UNESCO Clasification: Investigación
Keywords: Biometrics
Iris
Liveness
Sclera
Visible spectrum
Issue Date: 2016
Journal: Pattern Recognition Letters 
Abstract: In this research a new framework for software-based liveness detection for direct attacks in multimodal ocular biometrics across the visible spectrum is proposed. The framework aims to develop a more realistic method for liveness detection compared to previous frameworks proposed in the literature. To fulfil the above highlighted aims in this framework, intra-class level (i.e. user level) liveness detection is introduced. To detect liveness, a new set of image quality-based features is proposed for multimodal ocular biometrics in the visible spectrum. A variety of transformed domain (focus related) aspect and contrast-related quality features are employed to design the framework. Furthermore a new database is developed for liveness detection of multimodal ocular biometrics, which has the prominent presence of multimodal ocular traits (both sclera and iris). Moreover this database is comprised of a larger variety of fake images; those were prepared by employing versatile forging techniques which can be exhibited by imposters. Therefore the proposed schema has dealt with versatile categories of spoofing methods, which were not considered previously in the literature. The database contains a set of 500 fake and 500 genuine eye images acquired from 50 different eyes. An appreciable liveness detection result is achieved in the experiments. Furthermore, the experimental results conclude that this new framework is more efficient and competitive when compared to previous liveness detection schemes.
URI: http://hdl.handle.net/10553/55502
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2015.11.016
Source: Pattern Recognition Letters[ISSN 0167-8655],v. 82, p. 232-241
Appears in Collections:Artículos
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