Iris recognition is well suited to authentication on mobile devices, due to its intrinsic security and non-intrusiveness. However, authentication systems can be easily tricked by attacks based on high-quality printing. A liveness detection module is therefore necessary. Here, we propose a fast and accurate technique to detect printed-iris attacks based on the local binary pattern (LBP) descriptor. In order to improve the discrimination ability of LBP and better explore the image statistics, LBP is performed on a high-pass version of the image with 3 × 3 integer kernel. In addition a simplified interpolation-free descriptor is considered and finally a linear SVM classification scheme is used. The detection performance, measured on standard databases, is extremely promising, despite the resulting very low complexity, which makes possible the implementation for the relatively small CPU processing power of a mobile device.

Iris liveness detection for mobile devices based on local descriptors / Gragnaniello, Diego; Sansone, Carlo; Verdoliva, Luisa. - In: PATTERN RECOGNITION LETTERS. - ISSN 0167-8655. - 48:4(2015), pp. 1046-1054. [10.1016/j.patrec.2014.10.018]

Iris liveness detection for mobile devices based on local descriptors

GRAGNANIELLO, DIEGO;SANSONE, CARLO;VERDOLIVA, LUISA
2015

Abstract

Iris recognition is well suited to authentication on mobile devices, due to its intrinsic security and non-intrusiveness. However, authentication systems can be easily tricked by attacks based on high-quality printing. A liveness detection module is therefore necessary. Here, we propose a fast and accurate technique to detect printed-iris attacks based on the local binary pattern (LBP) descriptor. In order to improve the discrimination ability of LBP and better explore the image statistics, LBP is performed on a high-pass version of the image with 3 × 3 integer kernel. In addition a simplified interpolation-free descriptor is considered and finally a linear SVM classification scheme is used. The detection performance, measured on standard databases, is extremely promising, despite the resulting very low complexity, which makes possible the implementation for the relatively small CPU processing power of a mobile device.
2015
Iris liveness detection for mobile devices based on local descriptors / Gragnaniello, Diego; Sansone, Carlo; Verdoliva, Luisa. - In: PATTERN RECOGNITION LETTERS. - ISSN 0167-8655. - 48:4(2015), pp. 1046-1054. [10.1016/j.patrec.2014.10.018]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/595584
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 62
  • ???jsp.display-item.citation.isi??? 44
social impact