An Approach for Improving Security in Distance Education through Iris Recognition
In Distance Education the teacher and students are separated by time and distance; students can access their online courses by proper authentication methods. Student authentication in distance education has been a primary issue of federal policy makers. This paper describes the approach to strengthen student’s user IDs and passwords, by adding new Biometric technology to increase academic integrity and ensure proper use of federal student aid. This paper proposes a method combining traditional authentication (password and username) with biometric technology. To access the registration, participation, assessment, academic credit of distance education courses, Iris recognition used for authentication. Iris Recognition is a high-confidence biometric identification system with promising future in the security systems area. In this paper the features of a query images are compared with those of a database image to obtain matching scores. The features are extracted from the pre-processed images of iris. Iris Recognition uses Hamming Bit Distance (HBD) and Fragile Bit Distance (FBD) for matching process.
John Daugman “New Methods in Iris Recognition “ IEEE Transactions On Systems, Man, And Cybernetics-Part B: Cybernetics, Vol. 37, No.5, October 2007 .
Biometrics Security Concerns “Neha Dahiya, Dr. Chander Kant” IEEE Conference On Advanced Computing and Communication Technologies,2012. pg.no:297-302.
Nitin K. Mahadeo, Andrew P. Paplinski and Sid Ray “Model-Based Pupil and Iris Localization”IEEE World Congress On Computational Intelligence ,June 10-15,2012.
Peiming Du, Xiaoli Shi, NingningWang and Rongjun Deng “Iris Recognition Based On Principal Phase Congruency” IEEE Conference On Control And Decision2012 page:1159-1162.
Ifeanyi Ugbaga Nkole, Ghazali Bin Sulong “An Enhanced Iris Segmentation Algorithm Using Circle Hough Transform”International Conference on Informatics and Technology, November 2011.
W. W. Boles and B. Boashash “A Human Identication Technique Using Images of the Iris and Wavelet Transform” IEEE Transactions On Signal Processing, Vol. 46, NO. 4, APRIL 1998 .
Karen P. Hollingsworth, Kevin W. Bowyer and Patrick J.Flynn “Improved Iris Recognition Through Fusion Of Hamming Distance And Fragile Bit Distance”IEEE Transactions On Pattern Analysis and Machine Intelligence,Vol-33,No-12,Dec-2011.
Hussain.M.A. “Eigenspace based accurate iris recognition system” India Conference (INDICON), 2010 Annual IEEE
Vatsa. M, Singh. R ,Noore.A. “Improving Iris Recognition Performance Using Segmentation, Quality Enhancement, Match Score Fusion and Indexing” IEEE Transactions On Systems, Man, and Cybernetics, PARTB: Volume: 38 , Issue: 4, pg:1021 – 1035 , 2008.
Chung-Chih Tsai; Heng-Yi Lin; Taur, J.;Chin-Wang Tao “Iris Recognition Using Possibilistic Fuzzy Matching on Local Features “IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Volume: 42 , Issue: 1 , pg:150-162, 2012.
Wenbo Dong; Zhenan Sun; Tieniu Tan “Iris Matching Based on Personalized Weight Map “IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 33 , Issue: 9, pg: 1744 - 1757 , 2012.
Dey,S,Samanta.D “Iris Data Indexing Method Using Gabor Energy Features”IEEE Transactions on Information Forensics and Security, Volume: 7 , Issue: 4 , Page(s): 1192 – 1203, 2012
Chen.R,LinX.R,Ding.T.H. “Iris segmentation for non cooperative recognition systems”IEEE Transactions On Image Processing, IET Volume: 5 , Issue: 5 , Page(s): 448 – 456, 2011.
PadmaPolash.P, Maruf Monwar.M,”Human iris recognition for biometric Identification” 10th International Conference on Computer and information Technology, 2007.
Jafar M. H. Ali and Aboul Ella Hassanien, “A Human Iris Recognition Techniques to Enhance E-Security Environment Using Wavelet Transform,” In Proc. of the IADIS Int. Conf on www/internet Portugal, 2003, pp. 572-579.
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