Dynamic sectored random projection for cancelable iris template

Biometrics is an indispensable tool which is being used widely in sensitive authentication applications. The increase in usage of the biometrics has also raised several issues related to the security of the biometrics. Several template protection schemes have been introduced to secure the biometrics from being compromised. Cancelable biometrics is a template protection scheme which enables the biometrics to be revoked like a token or password. The enrolment and matching of the biometrics are performed in a transformed domain. A dynamic sectored random projection for cancelable iris template has been proposed. The technique projects the sectored iris features on a dynamic random projection matrix to generate a transformed template. The dynamic random projection matrix is derived with respect to the iris feature itself and no external key is required. The samples from IIT-Delhi iris and CASIA Iris image version 1.0 databases were used in the experiments. The matching performance, non-invertibility and distinctiveness of the transformed templates generated with the proposed technique, have been analyzed. The transformed templates generated using the proposed approach, have proved to be promising and satisfying the characteristics of cancelable biometrics.

[1]  Christoph Busch,et al.  Cancelable multi-biometrics: Mixing iris-codes based on adaptive bloom filters , 2014, Comput. Secur..

[2]  Nalini K. Ratha,et al.  Cancelable iris biometric , 2008, 2008 19th International Conference on Pattern Recognition.

[3]  Norimichi Tsumura,et al.  Tokenless Cancelable Biometrics Scheme for Protecting Iris Codes , 2010, 2010 20th International Conference on Pattern Recognition.

[4]  Andrew Beng Jin Teoh,et al.  Cancelable Biometrics Realization With Multispace Random Projections , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[5]  Heikki Mannila,et al.  Random projection in dimensionality reduction: applications to image and text data , 2001, KDD '01.

[6]  Andreas Uhl,et al.  Transforming Rectangular and Polar Iris Images to Enable Cancelable Biometrics , 2010, ICIAR.

[7]  Bhagavatula Vijaya Kumar,et al.  Biometric Encryption using image processing , 1998, Electronic Imaging.

[8]  Rama Chellappa,et al.  Sectored Random Projections for Cancelable Iris Biometrics , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[9]  Nalini K. Ratha,et al.  Generating Cancelable Fingerprint Templates , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Rama Chellappa,et al.  Secure and Robust Iris Recognition Using Random Projections and Sparse Representations , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Christoph Busch,et al.  On application of bloom filters to iris biometrics , 2014, IET Biom..

[12]  Anil K. Jain,et al.  Biometric Template Security , 2008, EURASIP J. Adv. Signal Process..

[13]  Dimitris Achlioptas,et al.  Database-friendly random projections , 2001, PODS.

[14]  John Daugman,et al.  How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.

[15]  W. B. Johnson,et al.  Extensions of Lipschitz mappings into Hilbert space , 1984 .

[16]  Christoph Busch,et al.  Dynamic random projection for biometric template protection , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[17]  Pritee Khanna,et al.  Gaussian Random Projection Based Non-invertible Cancelable Biometric Templates , 2015 .

[18]  Christian Callegari,et al.  Advances in Computing, Communications and Informatics (ICACCI) , 2015 .