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Efficient Small Template Iris Recognition System Using Wavelet Transform
Mohammed A. M. Abdullah, F. H. A. Al-Dulaimi, Waleed Al-Nuaimy, Ali Al-Ataby
Pages - 16 - 27     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 5   Issue - 1    |    Publication Date - March / April 2011   Table of Contents
Iris Recognition, Feature Extraction, Wavelet Transform
Iris recognition is known as an inherently reliable biometric technique for human identification. Feature extraction is a crucial step in iris recognition, and the trend nowadays is to reduce the size of the extracted features. Special efforts have been applied in order to obtain low templates size and fast verification algorithms. These efforts are intended to enable a human authentication in small embedded systems, such as an Integrated Circuit smart card. In this paper, an effective eyelids removing method, based on masking the iris, has been applied. Moreover, an efficient iris recognition encoding algorithm has been employed. Different combination of wavelet coefficients which quantized with multiple quantization levels are used and the best wavelet coefficients and quantization levels are determined. The system is based on an empirical analysis of CASIA iris database images. Experimental results show that this algorithm is efficient and gives promising results of False Accept Ratio (FAR) = 0% and False Reject Ratio (FRR) = 1% with a template size of only 364 bits.
CITED BY (8)  
1 Abdullah, M. A., Chambers, J. A., Woo, W. L., & Dlay, S. S. (2015). Iris Biometric: Is the Near-Infrared Spectrum always the Best?.
2 Al-Zubi, R. T., Darabkh, K. A., & Al-Zubi, N. (2015). Effect of Eyelid and Eyelash Occlusions on a Practical Iris Recognition System: Analysis and Solution. International Journal of Pattern Recognition and Artificial Intelligence, 29(08), 1556016.
3 Vera, D. F., Cadena, D. M., & Ramirez, J. M. (2015, September). Iris recognition algorithm on BeagleBone Black. In Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2015 IEEE 8th International Conference on (Vol. 1, pp. 282-286). IEEE.
4 Abdullah, M. A., Dlay, S. S., & Woo, W. L. (2014, November). Fast and Accurate Pupil Isolation Based on Morphology and Active Contour. In The 4th International conference on Signla, Image Processing and Applications (pp. 418-420).
5 Abdullah, M., Dlay, S. S., & Woo, W. L. (2014, October). Fast and accurate method for complete iris segmentation with active contour and morphology. In Imaging Systems and Techniques (IST), 2014 IEEE International Conference on (pp. 123-128). IEEE.
6 Al-Zubi, R. T., Darabkh, K. A., & Jararweh, Y. I. (2014). A Powerful Yet Efficient Iris Recognition Based on Local Binary Quantization. Information Technology And Control, 43(3), 244-251.
7 Zhang, Y., Laurikkala, J., & Juhola, M. (2014). Biometric verification of a subject with eye movements, with special reference to temporal variability in saccades between a subject’s measurements. International Journal of Biometrics, 6(1), 75-94.
8 Zhang, Y., Rasku, J., & Juhola, M. (2012). Biometric verification of subjects using saccade eye movements. International Journal of Biometrics, 4(4), 317-337.
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Mr. Mohammed A. M. Abdullah
University of Mosul - Iraq
Dr. F. H. A. Al-Dulaimi
University of Mosul - Iraq
Dr. Waleed Al-Nuaimy
University of Liverpool - United Kingdom
Mr. Ali Al-Ataby
University of Liverpool - United Kingdom