Image quality assessment for fake biometric detection: Application to Iris, fingerprint, and face recognition
Entidad
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesEditor
IEEEFecha de edición
2014-02-01Cita
10.1109/TIP.2013.2292332
IEEE Transactions on Image Processing 23.2 (2014): 710 - 724
ISSN
1057-7149 (print); 1941-0042 (online)DOI
10.1109/TIP.2013.2292332Financiado por
This work has been partially supported by projects Contexts (S2009/TIC-1485) from CAM, Bio-Shield (TEC2012-34881) from Spanish MECD, TABULA RASA (FP7-ICT-257289) and BEAT (FP7-SEC-284989) from EU, and Cátedra UAM-TelefónicaProyecto
info:eu-repo/grantAgreement/EC/FP7/257289; info:eu-repo/grantAgreement/EC/FP7/284989; Comunidad de Madrid. S2009/TIC-1485/CONTEXTSVersión del editor
J. Galbally, S. Marcel and J. Fierrez, "Image quality assessment for fake biometric detection: Application to Iris, fingerprint, and face recognition", IEEE Transactions on Image Processing, vol. 23, no. 2, pp. 710-724, February 2014. http://dx.doi.org/10.1109/TIP.2013.2292332Materias
attacks; biometrics; countermeasures; Image quality assessment; security; TelecomunicacionesNota
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© 2014 IEEEResumen
To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.
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Google Scholar:Galbally Herrero, Javier
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Marcel, Sébastien
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Fiérrez Aguilar, Julián
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Chingovska, Ivana; Yang, Jinyi; Lei, Zhen; Yi, Dong; Li, Stan; Kahm, Olga; Glaser, Christian; Darner, N.; Kuijper, Arjan; Nouak, Alexander; Komulainen, Jukka; Pereira, Tiago F.; Gupta, Saurabh R.; Khandel Wa, S.; Bansal, Shubham K.; Rai, A.; Krishna, Tarun Murali Ajay; Goyal, Dushyant; Waris, Muhammad Adeel; Zhang, H.; Ahmad, Iftikhar; Kiranyaz, Serkan; Gabbouj, Moncef; Tronci, Roberto; Pili, Michela; Sirena, Nicola; Roli, Fabio; Galbally Herrero, Javier; Fiérrez Aguilar, Julián; Da Silva Pinto, Allan; Pedrini, Hélio; Schwartz, W. S.; Rocha, Antonio A De A; Anjos, André Rabello Dos; Marcel, Sébastien
2013