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Comparison of Edge Detection Techniques for Iris Recognition

by Satbir Kaur, Ishpreet Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 149 - Number 9
Year of Publication: 2016
Authors: Satbir Kaur, Ishpreet Singh
10.5120/ijca2016911572

Satbir Kaur, Ishpreet Singh . Comparison of Edge Detection Techniques for Iris Recognition. International Journal of Computer Applications. 149, 9 ( Sep 2016), 42-47. DOI=10.5120/ijca2016911572

@article{ 10.5120/ijca2016911572,
author = { Satbir Kaur, Ishpreet Singh },
title = { Comparison of Edge Detection Techniques for Iris Recognition },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 149 },
number = { 9 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 42-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume149/number9/26028-2016911572/ },
doi = { 10.5120/ijca2016911572 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:54:19.543140+05:30
%A Satbir Kaur
%A Ishpreet Singh
%T Comparison of Edge Detection Techniques for Iris Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 149
%N 9
%P 42-47
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays security and authentication are the foremost parts of our daily life. Iris is the one of the most reliable organ or part of the human body which can be used for identification and authentication purpose. This paper examines for edge detection techniques use for iris recognition system .Between the prewitt,sobel,LoG,Min.contructor of laplacian edge detector techniques the experimental results show that minimum constructor of laplacian edge detector(Hybrid) has better ability to detect edges in digital image.

References
  1. Daouk, C.H., El-Esber, L.A., Kammoun, F.D. and Al Alaoui, M.A. (2002) Iris Recognition. IEEE ISSPIT, Marrakesh, 1.
  2. Tuama, A.S. (2012) Iris Image Segmentation and Recognition. International Journal of Computer Science & EmergingTechnologies, 3, 60-65.
  3. Shashi Kumar, D.R., Raja, K.B., Chhootaray, R.K. and Pattnaik, S. (2011) PCA Based Iris Recognition Using DWT. International Journal of Computer Technology and Applications, 2,pp. 884-893
  4. Dewangan, A.K. and Siddhiqui, M.A. (2012) Human Identification and Verification Using Iris Recognition by Calculating Hamming Distance. International Journal of Soft Computing and Engineering (IJSCE), 2,pp. 334-338.
  5. Santos, G. and Hoyle, E. (2012) A Fusion Approach to Unconstrained IrisRecognition. Pattern Recognition Letters, 33,pp.984990.http://dx.doi.org/10.1016/j.patrec.2011.08.017
  6. Daugman, J., “Complete Discrete 2-D Gabor Transforms by Neural Networks for Image Analysis and Compression”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 36, no. 7, July 1988, pp. 1169-1179.
  7. Daugman,J. “How Iris Recognition Works”, available at http://www.ncits.org/tc_home//m1htm/docs/m1020044.pdf.
  8. Daugman, J., “High Confidence Visual Recognition of Persons by a Test of Statistical Independence,”IEEE transactions on pattern analysis and machine intelligence, vol. 15, no.11, November 1993, pp. 1148-1161.
  9. W. Frei and C. Chen, "Fast Boundary Detection: A Generalization and New Algorithm," IEEE Trans. Computers, vol. C-26, no. 10, pp. 988-998, Oct. 1977.
  10. J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698, Nov. 1986
  11. Raman Maini and Dr. Himanshu Aggarwal “Study and Comparison of various Image Edge Detection Techniques” International Journal of Image Processing (IJIP), Vol3: Issue (1).
  12. S.Lakshmi and Dr.V.Sankaranarayanan “A study of Edge Detection Techniques for Segmentation Computing Approaches” IJCA Special Issue on Imaging and Biomedical Applications” CASCT, 2010. Edge Detection by Trucco,Chapter 4 and Jain ctal.,Chapter5
  13. Zolqemine Othman, habibollahharon, Mohammed Rafi, Abdul kadir, ―Comparison of canny and Sobel edge detection in mri images.
  14. M sudarsha*” p ganga Mohan and suryakanth v gangashetty ―Optimized edge detection algorithm for face recognition”.
  15. Lye Wil Liam, Chekima, A., Liau Chung Fan, and Dargham, J.A., “Iris recognition using selforganizing neural network,” IEEE, Student Conference on Research and Developing Systems, Malaysia, pp. 169–172, 2002
  16. Proenca H. and Alexandre L.A., “Iris segmentation methodology for non-cooperative recognition,” IEE Proc.Vis.Image Signal Processing, Vol. 153, No. 2, Pp.199-205, 2006.
  17. J. Daugman, “How Iris Recognition Works”, Proceedings of 2002 International Conference on Image Processing, Vol. 1, 2002.
  18. R.P. Wildes,, Asmuth, J.C. et al., “A System for Automated Iris Recognition”, Proc of the Second IEEE Workshop on Applications of Computer Vision, 1994, pp.121 -128
  19. C. Tisse, L. Martin, L. Torres and M. Robert, “Person identification technique using human iris recognition”, St Journal of System Research , 2003, Vol. 4, pp. 67-75
  20. W. Boles and B. Boas hash, “A Human Identification Technique Using Images of the Iris and Wavelet Transform,” IEEE Trans. on Signal Processing, vol. 46, no. 4, pp.1185-1188, 1998.
  21. R. Wildes, J. Asmuth, G. Green, S. Hsu, R. Kolczynski, J. Matey, S. McBride, “A Machine-vision System for Iris Recognition,” vol. 9, pp.1-8, 1996.
  22. Jain, A., Hong, L., and Pankanti, S. (2000). Biometric identification. Communications of the ACM, 43(2),pp.90–98.
  23. Vatsa, M., Singh, R., and Noore, A. (2008). Improving iris recognition performance using segmentation, quality enhancement, match score fusion, andindexing. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 38(4),pp.1021–1035.
  24. Chen, W., Er, M. J., and Wu, S. (2006). Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 36(2),pp.458–466
  25. EdurneBarrenechea, HumbertoBustince, Member, IEEE, Bernard De Baets,And Carlos Lopez-Molina, Student Member, IEEE, “Construction Of Interval-Valued Fuzzy Relations With Application To The Generation Of Fuzzy Edge Images”, IEEE Transactions On Fuzzy Systems, Vol. 19, No. 5, October 2011, pp. 819-830.
  26. Abdallah A. Alshennawy, and Ayman A. Aly, "Edge Detection Indigital Images Using Fuzzy Logic Technique", World Academy Of Science Engineering And Technology 51, 2009, pp. 178-186.
  27. U.G.Sefercik, O.E.Gulegen, “Edge Detection in geologic formation extraction: Close range and remote sensing Case studies”
  28. H. Voorhees and T. Poggio,” Detecting textons and texture boundries in natural images” ICCV 87:250-25, 1987
  29. Pinaki Pratim Acharjya, Ritaban Das and Dibyendu Ghoshal, “Study and Comparison of Different Edge Detectors for Image Segmentation”, Global Journal of Computer Science and Technology Graphics & Vision, Online ISSN: 0975-4172 & Print ISSN: 0975-4350, Volume 12 Issue 13 Version 1.0 Year 2012
  30. Nisha, Rajesh Mehra and Lalita Sharma “Comparative Analysis of Canny and Prewitt Edge Detection Techniques used in Image Processing”, International Journal of Engineering Trends and Technology (IJETT) –Volume 28 Number 1 - October 2015
Index Terms

Computer Science
Information Sciences

Keywords

Sobel Prewitt LoG Min.constructor of laplacian edge detector(Hybrid) SSIM

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