CFP last date
20 December 2024
Reseach Article

Effect on Iris Recognition by Image Compression SPIHT and JPEG 2000

Published on None 2011 by Anvita Birje, Shoba Krishnan
journal_cover_thumbnail
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET - Number 1
None 2011
Authors: Anvita Birje, Shoba Krishnan
5fa82504-e5a4-4d03-ba1f-7862042acd9f

Anvita Birje, Shoba Krishnan . Effect on Iris Recognition by Image Compression SPIHT and JPEG 2000. International Conference and Workshop on Emerging Trends in Technology. ICWET, 1 (None 2011), 1-8.

@article{
author = { Anvita Birje, Shoba Krishnan },
title = { Effect on Iris Recognition by Image Compression SPIHT and JPEG 2000 },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { None 2011 },
volume = { ICWET },
number = { 1 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 1-8 },
numpages = 8,
url = { /proceedings/icwet/number1/2063-aca134/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A Anvita Birje
%A Shoba Krishnan
%T Effect on Iris Recognition by Image Compression SPIHT and JPEG 2000
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET
%N 1
%P 1-8
%D 2011
%I International Journal of Computer Applications
Abstract

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is one of techniques used to identify people and gives the most accurate and secure means of biometric identification. The biometric authentication technique is based on the pattern of the human iris. This makes the technology very useful in areas such as information security, physical access security, ATMs and airport security with the increasing need of the biometric systems there is the need of large databases of iris images. If required storage space is not adequate for these images, compression is an alternative. It allows a reduction in the space needed to store these iris images, although it may the cost of some amount of information lost in the process and therefore the solution is Image Compression.

References
  1. A. Said, W. A. Pearlman, “A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 6, No. 3, pp. 243-249, June 1996
  2. A. Said, W. A. Pearlman, “SPIHT Image Compression: Properties of the Method”, http://www.cipr.rpi.edu/research/SPIHT/spiht1.html
  3. B. Carpentieri, M. J.Weinberger, G. Seroussi, “Lossless Compression of Continuous-Tone Images”, Proceedings of IEEE, Vol.88, No.11, pp.1797-1807, November 2000
  4. Chinese Academy of Sciences – Institute of Automation. Database of 756 Greyscale Eye Images. http://www.sinobiometrics.com Version 1.0, 2003.
  5. J. Daugman. “How iris recognition works”. Proceedings of 2002 International Conference on Image Processing, Vol. 1, 2002.
  6. Karen L. Gray, “The JPEG2000 Standard”.
  7. L. Masek, “Recognition of Human Iris Patterns for Biometric Identification,” M. Thesis, The University of Western Australia, 2003, www.csse.uwa.edu.au/~pk/studentprojects/libor/LiborMasekThesis.pdf, Mar. 26, 2005
  8. R.W.Ives, B. L. Bonney, D.M. Etter. “Effect of Image Compression on iris recognition”. IEEE Transactions IMTC 2005.Ottawa, Canada, 17-19 May 2005.
  9. S. Grgic, K. Kers, M. Grgic, “Image Compression Using Wavelets”, Proceedings of the IEEE International Symposium on Industrial Electronics, ISIE'99, Bled, Slovenia, pp. 99-104, 1999
  10. J. M. Shapiro, “Embedded Image Coding Using Zerotrees of Wavelet Coefficients,” IEEE Transactions on Signal Processing, Vol. 41, pp.3445-3462, December 1993
Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Iris recognition Image Compression SPIHT JPEG2000