Abstract
To enable cancelable biometrics, we apply two classical transformations, block re-mapping and texture warping, in two variants to iris image data: first, the transformations are applied to rectangular iris imagery prior to iris detection and iris texture unwrapping, and second, the transformations are applied to polar iris images after the generation of the corresponding iris texture patch. The CASIA V3 Iris database is used and experimental results on the matching performance and key sensitivity of a popular iris recognition method employing the cancelable transforms are given.
This work has been partially supported by the Austrian Science Fund, project no. L554-N15.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ratha, N., Connell, J., Bolle, R.: Enhancing security and privacy in biometrics-based authentication systems. IBM Systems Journal 40(3), 614–634 (2001)
Chong, S.C., Jin, A.T.B., Ling, D.N.C.: High security iris verification system based on random secret integration. Computer Vision and Image Understanding 102(2), 169–177 (2006)
Chong, S.C., Jin, A.T.B., Ling, D.N.C.: Iris authentication using privatized advanced correlation filter. In: Proceedings of the 1st International IAPR Conference on Biometrics (ICB’06). Volume 4642 of Springer Lecture Notes on Computer Science. (2006) 382–388
Zuo, J., Ratha, N.K., Connel, J.H.: Cancelable iris biometric. In: Proceedings of the 19th International Conference on Pattern Recognition 2008 (ICPR’08), pp. 1–4 (2008)
Hämmerle-Uhl, J., Pschernig, E., Uhl, A.: Cancelable iris biometrics using block re-mapping and image warping. In: Samarati, P., Yung, M., Martinelli, F., Ardagna, C.A. (eds.) ISC 2009. LNCS, vol. 5735, pp. 135–142. Springer, Heidelberg (2009)
Dobeš, M., Machala, L., Tichavský, P., Pospíšil, J.: Human eye iris recognition using the mutual information. Optik 115(9), 399–405 (2006)
Wolberg, G.: Image morphing: a survey. The Visual Computer 14(8/9), 360–372 (1998)
Bowyer, K., Hollingsworth, K., Flinn, P.: Image understanding for iris biometrics: A survey. Computer Vision and Image Understanding 110(2), 281–307 (2008)
Daugman, J.: How iris recognition works. IEEE Transactions on Circiuts and Systems for Video Technology 14(1), 21–30 (2004)
Ma, L., Tan, T., Wang, Y., Zhang, D.: Efficient iris recognition by characterizing key local variations. IEEE Transactions on Image Processing 13, 739–750 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Färberböck, P., Hämmerle-Uhl, J., Kaaser, D., Pschernig, E., Uhl, A. (2010). Transforming Rectangular and Polar Iris Images to Enable Cancelable Biometrics. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13775-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-13775-4_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13774-7
Online ISBN: 978-3-642-13775-4
eBook Packages: Computer ScienceComputer Science (R0)