International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 6, No. 9, 8 Aug. 2014
Cover page and Table of Contents: PDF (size: 696KB)
Iris Biometric Authentication used for Security Systems
Full Text (PDF, 696KB), PP.54-60
Views: 0 Downloads: 0
Author(s)
Index Terms
Feature extraction, haar wavelet transformation, FAR, FRR, Feature vector size, Computational time
Abstract
Pupil detection and iris localisation using scanning method and feature extraction is performed with five level decomposition techniques, with these two proposed algorithm we could achieve efficient and fast person authentication in biometric security systems. Statistical performance evaluation is also performed using parameters False acceptance rate (FAR), False rejection rate (FRR), Correct recognition rate (CRR), Equal error rate (EER), Match ratio etc, using CASIA database.
Cite This Paper
Vanaja Roselin.E.Chirchi, Laxman.M.Waghmare,"Iris Biometric Authentication used for Security Systems", IJIGSP, vol.6, no.9, pp.54-60, 2014. DOI: 10.5815/ijigsp.2014.09.07
Reference
[1]A. Poursaberi and H. N. Araabi, (2005),” Iris Recognition for Partially Occluded Methodology and Sensitivity Analysis”, EURASIP journal on Advances in Signal processing, Vol. 2007, Article ID 36751.
[2]A.Poursaberi and B.N.Araabi (2005),” A Half Eye Wavelet Based for Iris Recognition”, proceeding of the 2005, 5th International Conference on Intelligent Systems Design and Applications (ISDA’05.
[3]Amol D. Rahulkar, R.S. Holambe Feb 2012, ”Half-Iris Feature Extraction and Recognition using a New Class of Biorthogonal triplet Half-Band Filter Bank and Flexible k-out-of-n: A postclassifier”, IEEE Transactions on Information Forensics and Security, Vol. 7, No.1.
[4]J.Daugman (2002), “How Iris Recognition works”, proceedings of 2002 International conference on Image processing, vol.1.
[5]J.Daugman Jan 2004, “How Iris Recognition works, IEEE Transactions on Circuits and systems for video Technology”, Vol. 14, No. 1.
[6]J.Daugman (2001), “Statistical Richness of Visual Phase Information: Update on recognizing persons by Iris patterns”, International Journal of computer vision, Vol.45, No.1, pp.25-38.
[7]Jafar M. H. Ali, Aboul Ella Hassanien, (2003), “An Iris Recognition System to Enhance E-security Environment Based on Wavelet Theory”, AMO-Advance Modeling and Optimization, vol. 5, No. 2
[8]John Daugman, (Nov 2006),” Probing the Uniqueness and Randomness of IrisCodes: Results from 200 Billion Iris Pair Comparisons”, Proceedings of the IEEE, Vol. 94, Issue: 11, pages: 1927-1935.
[9]L.Ma, Y.wang, T.Tan (2002), “Iris recognition Based on multichannel Gabor Filtering”, Proc. of the 5th Asian conference on computer vision, vol.I, pp.279-283.
[10]L.Ma, Y.wang, T.Tan(2002), “Iris Recognition using Circular Symmetric Filters”, proc. of the 16th International Conference on pattern recognition, vol.II, pp.414-417.
[11]Li Ma, T. Yunhong Wang, and D. Zhang, (2003), “Personal identification based on iris texture analysis”, IEEE Transactions on Pattern Analysis and machine Intelligence, vol.25, no.12.
[12]Li Ma, Tieniu Tan, Yunhong Wang and Dexin Zhang, (June 2004), “Efficient Iris Recognition by Characterizing Key Local Variations”, IEEE Transactions on Image processing, Vol. 13, No.6.
[13]Li. Ma, et al. (2004), “Local Intensity Variation Analysis for Iris Recognition”, Elsevier- Pattern Recognition, vol.37, No.6, pp.1287-1298.
[14]Mayank vatsa, Richa singh, Afzel Noore (Aug. 2008),” Improving Iris recognition performance using segmentation, Quality Enhancement”, Match Score Fusion, and Indexing, IEEE Transactions on Systems, Man, and Cybernetics B, Cybern., vol. 38, no. 4, pp.1021-1034.
[15]R.P.wildes (1999),” Iris Recognition: An Emerging Biometric Technology”, Proceeding of the IEEE, vol. 85, pp 1348-1363.
[16]R.Wildes, J.Asmuth, G. Green,S. Hsu, R. Kolczynski, J. Matey and S.McBride(1996), “ A machine-vision system for Iris Recognition”, Machine vision and Applications, vol.9, pp1-8.
[17]Richard Yew Fatt Ng, Yong Hour Tay, Kai Ming Mok 2007, “A Review if Iris Recognition Algorithm”, IEEE Transaction, DOI 978-1-4244-2328-6/08.
[18]S.Lim, K. Lee, O. Byeon, T. Kim, (June 2001),” Efficient Iris Recognition through Improvement of Feature Vector and Classifier”, ETRI Journal, Vol. 23, No. 2, pp. 61-70.
[19]W.Boles and B.Boashash, (April 1998), “A Human Identification Technique using Images of the Iris and wavelet transform”, IEEE Transactions on signal processing, Vol. 46, No. 4.
[20]http://www.sinobiometrics.com/resources.htm.
[21]Md. Rabiul Islam, Dr. Wang Yin Chai, Asma Khatun (2010), “Partial Iris Image Recognition Using Wavelet Based Texture Features”, International Conference on Intelligent and Advance Systems (ICIAS).
[22]V.K.Narendira Kumar, Dr.B.Srinivasan” Performance of personal Identification system technique using Iris Biometric Technology”, IJIGSP- MECS Publication, Vol.5, Pg No. 63-71, April 2013.