Information Security in E-Learning through Identification of Humans

Authors: Hassan Haleh, Zohreh Nasiri, Parisa Farahpour

Abstract:

During recent years, the traditional learning approaches have undergone fundamental changes due to the emergence of new technologies such as multimedia, hypermedia and telecommunication. E-learning is a modern world phenomenon that has come into existence in the information age and in a knowledgebased society. E-learning has developed significantly within a short period of time. Thus it is of a great significant to secure information, allow a confident access and prevent unauthorized accesses. Making use of individuals- physiologic or behavioral (biometric) properties is a confident method to make the information secure. Among the biometrics, fingerprint is more acceptable and most countries use it as an efficient methods of identification. This article provides a new method to compare the fingerprint comparison by pattern recognition and image processing techniques. To verify fingerprint, the shortest distance method is used together with perceptronic multilayer neural network functioning based on minutiae. This method is highly accurate in the extraction of minutiae and it accelerates comparisons due to elimination of false minutiae and is more reliable compared with methods that merely use directional images.

Keywords: Fingerprint, minutiae, extraction of properties, multilayer neural network

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1074724

References:

[1] a.zahedpoor," a new method for fingerprint matching with neural network", 4th security conferences, industry Iran University, 2007.
[2] p.jafari,"fingerprint classifying with artificial intelligence methods m.sc thesis, Tabriz university, 2006.
[3] R.Ross,A.Jain, "From Template to Image: Reconstructing fingerprints From Minutiae Points", IEEE Transactions On Pattern Analysis and Machine Intelligence, Vol. 29, No. 4, April 2007.
[4] D. Miao, Q. Tang, "Fingerprint Minutiae Extraction Based On Principal Curves ", Department Of Computer Science and Engineering, Tongji University, 2004.
[5] T. Ohtsuka, A. Kondo, "A New Approach to Detect Core and Delta of the Fingerprint Using Extended Relationalgraph, "Ieee Proc. Of 2005 Icip, Vol. 3, Pp. 249-252, 2005.
[6] Xiping, T.Jie, W.Yan, "A Minutia Matching Algorithm In Fingerprint Verification," Pattern Recognition, International Conference Pattern On Recognition Vol. 4, Pp. 4833, 2000.
[7] S.Greenberg, D.Kogan,"Fingerprint Image Enhancement Using Filtering Techniques", Electrical And Computer Engineering Department, Ben-Gurion University Of The Negev, Beer-Sheva 2001.
[8] R. Ramli,A. Rosaliza,"A Segmentation Algorithm Based-On Histogram Equalizer For Fingerprint Classification System", Second International Conference On Electrical And Computer Engineering Icece, PP.26-28, December 2002
[9] L.Hong, Y.wan, Anil Jain, "Fingerprint Image Enhancement: Algorithm and Performance Evaluation", Ieee Transactions On Pattern Analysis And Machine Intelligence, Vol. 20, No8, PP.777-789, August 1998.
[10] Philips D. ,Wang Y. ,"A Fingerprint Orientation Model Based On 2D Fourier Expansion And Its Application", Ieee, Tran, Pattern Analysis And Machine Intelligence,Vol29 , No4,PP.573-585 ,April 2007
[11] D.Maio,R.Cappelli," Fingerprint Classification by Directional Image Partitioning", IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 21, No. 5, May 1999
[12] J.W. Yang, L.F. Liu, and T.Z. Jiang, Y. Fan, "A modified Gabor Filter Design Method for Fingerprint Image Enhancement, "Pattern Recognition, PP.1805-1817, 2003.
[13] C.Hong, L.Miao,"A Gabor Filter Based Fingerprint Enhancement Algorithm in Wavelet Domain", Communications and Information Technology, Vol. 2, PP.1468-1471, October 2005.