A review on “Removing the effect of contact lens in IRIS recognition

Miss. Sable Jyoti P. and Prof.Mulajkar R.M.

doi:https://doi.org/10.14445/23488549/IJECE-V3I7P102

Research Article | Open Access

Volume 3 | Issue 7 | Year 2016 | Article Id. IJECE-V3I7P102 | DOI : https://doi.org/10.14445/23488549/IJECE-V3I7P102

A review on “Removing the effect of contact lens in IRIS recognition"

Miss. Sable Jyoti P. and Prof.Mulajkar R.M.

Citation :

Miss. Sable Jyoti P. and Prof.Mulajkar R.M., "A review on “Removing the effect of contact lens in IRIS recognition"," International Journal of Electronics and Communication Engineering, vol. 3, no. 7, pp. 1-4, 2016. Crossref, https://doi.org/10.14445/23488549/IJECE-V3I7P102

Abstract

Over the years, iris recognition has gained importance in the biometrics applications and is being used in several large scale nationwide projects. Though iris patterns are unique, they may be affected by external factors such as illumination, camera-eye angle, may also pose a challenge to iris biometrics as it obfuscates the iris patterns and changes the inter and intraclass distributions. This paper presents an in-depth analysis of the effect of contact lens on iris recognition performance. The presence of contact lens, particularly color cosmetic lens, However, further research is required to build sophisticated lens detection algorithm that can improve iris recognition.

Keywords

Introduction, Iris Recognition, Contact Lens, Lens Detection, conclusion.

References

[1] S. S. Arora, M. Vatsa, R. Singh, and A. K. Jain. On iris camera interoperability. In BTAS, pages 346–352, 2012.
[2] S. E. Baker, A. Hentz, K.W. Bowyer, and P. J. Flynn. Contact lenses: handle with care for iris recognition. In BTAS, pages 190– 197, 2009.
[3] S. E. Baker, A. Hentz, K.W. Bowyer, and P. J. Flynn. Degradation of iris recognition performance due to non-cosmetic Prescription contact lenses. Computer Vision and Image Understanding, 114(9):1030–1044, 2010.
[4] R. Connaught on, A. Sgroi, K. Bowyer, and P. Flynn. A multialgorithm analysis of three iris biometric sensors. IEEE Transactions on Information Forensics and Security, 7(3):919–931, 2012.
[5] J. Daugman. Demodulation by complex-valued wavelets for stochastic pattern recognition. IJWMIP, 1:1–17, 2003.
[6] J. S. Doyle, P. J. Flynn, and K. W. Bowyer. Automated classification of contact lens type in iris images. IAPR 6th International Conference on Biometrics, 2013.
[7] X. He, S. An, and P. Shi. Statistical texture analysis-based approach for fake iris detection using support vector machines. In ICB, pages 540–546, 2007.
[8] K. Hollingsworth, K.W. Bowyer, and P. J. Flynn. Pupil dilation degrades iris biometric performance. Computer Vision and Image Understanding, 113(1):150–157, 2009.
[9] J. W. Thompson, H. Santos-Villalobos, P. J. Flynn, and K. W. Bowyer, “Effects of Iris surface curvature on Iris recognition,” in Proc. 6th IEEE Int. Conf. Biometrics, Technol., Appl., Syst., 2013, pp. 1–3.
[10] S. Baker, A. Hentz, K. Bowyer, and P. Flynn, “Degradation of Iris recognition performance due to non-cosmetic prescription contact lenses,” Comput. Vis. Image Understand., vol. 114, no. 9, pp. 1030–1044, 2010.
[11] J. Daugman, “Demodulation by complex-valued wavelets for stochastic pattern recognition. pattern recognition,” Int. J. Wavelets, Multiresolution Inf. Process., vol. 1, no. 1, pp. 1–17, 2003.