The week's pick
Random Articles
Reseach Article
A WPD Scanning Technique for Iris Recognition
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 85 - Number 14 |
| Year of Publication: 2014 |
| Authors: Ahmad M. Sarhan |
10.5120/14907-3446
|
Ahmad M. Sarhan . A WPD Scanning Technique for Iris Recognition. International Journal of Computer Applications. 85, 14 ( January 2014), 6-12. DOI=10.5120/14907-3446
Abstract
In this paper, we propose an algorithm that scans the WPD coefficients in a way that preserves the amplitudes and relative locations of certain high –magnitude approximation coefficients while discarding the rest of the transform coefficients. The proposed WPD scanning technique greatly improves the feature extraction capabilities of the standard WPD transform. When tested on the iris recognition problem using the CASIA database and the ANN classifier, the proposed system produces zero classification error and always outperforms the standard WPD system.
References
- R. Clarke, "Human identification in information systems: Management, challenges, and public policy issues," Information Technology & People, 7(4):6-37, 1994.
- J. Daugman, "High confidence visual recognition of persons by a test of statistical independence," IEEE. Transactions on Pattern Analysis and Machine Intelligence, 15(11): 1148–1161, 1993.
- J. Daugman, "Statistical richness of visual phase information: update on recognizing persons by iris patterns," International Journal on Computer Vision, 45 (1): 25–38, 2001.
- J. Daugman, " Probing the uniqueness and randomness of Iris codes: results from 200 billion iris pair comparisons," Proc. IEEE, 94 (11):1927–1935, 2006.
- H. B. kekre, S. D. Thepade, J. Jain and N. Agrawal, "IRIS recognition using texture features extracted from Haarlet pyramid", International Journal of Computer Applications, 11(12):1–5, 2010.
- A. M. Sarhan, "Iris recognition using the discrete cosine transform and artificial neural networks," Journal of Computer Science, 5(5):369–373, 2009.
- M. Vatsa, R. Singh, and P. Gupta, " Comparison of iris recognition algorithms," in International Conference on Intelligent Sensing and Information Processing, pp. 354–358, 2004.
- H. Proenca and L. A. Alexandre, "Iris segmentation methodology for non-cooperative recognition," in IEEE Proceedings on Vision, Image and Signal Processing, vol. 153, pp. 199–205, April 2006.
- H. Proença, "An iris recognition approach through structural pattern analysis methods," Expert Systems, 27(3):146–155, 2010.
- National Institute of Standards and Technology, Iris Challenge Evaluation, 2006. Available from :< http://iris. nist. gov/ICE>.
- Z. Wei, T. Tan, and Z. Sun, "Synthesis of large realistic Iris databases using patch-based sampling," Proc. Int. Conf. Pattern Recognition, pp. 1–4, 2008.
- P. V. C. Hough, "Machine Analysis of Bubble Chamber Pictures," Proc. Int. Conf. High Energy Accelerators and Instrumentation, 1959.
- R. O. Duda and P. E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Communications of the ACM, 15:11–15, 1972.
- S. Haykin," Neural networks: a comprehensive foundation," Macmillan, New York 1994.
Index Terms
Keywords