We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition

Published on March 2012 by H B Kekre, V A Bharadi
journal_cover_thumbnail

International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET2012 - Number 3
March 2012
Authors: H B Kekre, V A Bharadi
70ba8e0a-1096-4d9f-8061-283517437881

H B Kekre, V A Bharadi . Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition. International Conference and Workshop on Emerging Trends in Technology. ICWET2012, 3 (March 2012), 18-24.

@article{
author = { H B Kekre, V A Bharadi },
title = { Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { March 2012 },
volume = { ICWET2012 },
number = { 3 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 18-24 },
numpages = 7,
url = { /proceedings/icwet2012/number3/5329-1020/ },
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 H B Kekre
%A V A Bharadi
%T Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET2012
%N 3
%P 18-24
%D 2012
%I International Journal of Computer Applications
Abstract

Feature vector generation is an important step in biometric authentication. Biometric traits such as fingerprint, palmprint, iris, & finger-knuckle prints are rich in texture. This texture is unique and the feature vector extraction algorithm should correctly represent the texture pattern. In this paper a texture feature extraction methodology is proposed for iris and pamlprints. This method is based on one step transform of the two dimensional images and then using the intermediate transformation data to generate complex planes for feature vector generation. This method is implemented using Walsh, DCT, Hartley, Kekre Transform &Kekre Wavelets. Results indicate the effectiveness of the feature vector for biometric authentication.

References
  1. A. K. Jain, A. Ross, S. Prabhakar, “An Introduction to Biometric Recognition”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 1, January 2004
  2. H. B. Kekre, T. K. Sarode, R. Vig, "Fingerprint Matching using Sectorized Complex Walsh Plane in Transform Domain", Proceedings of ICWET 2011, ACM International Conference, Mumbai, India, Feb. 2011
  3. H. B. Kekre, V. A. Bharadi , “ Using Component Object Model for Interfacing Biometrics Sensors to Capture Multidimensional Features” , International Journal of Intelligent Information Technology Application (IJIITA), ISSN 1999-2459 (Print), China, Volume 2, No. 6, pp. 279-285, December 2009
  4. Hong Kong University PolyUDatabase : www4.comp.polyu. edu.hk/~biometrics/2D_3D_Palmprint.htm
  5. Phoenix Iris Database: http://phoenix.inf.upol.cz/iris/ download
  6. H. B Kekre, V A Bharadi, “Biometric Authentication Systems”, Ph. D. Thesis Submitted to NMIMS University, June 2011
  7. H. F. Harmuth, “Applications of Walsh Functions in Communications." IEEE Spectrum 6, pp. 82-91, 1969
  8. H. B. Kekre, T. K. Sarode, R. Vig, "Fingerprint Matching using Sectorized Complex Walsh Plane in Transform Domain", Proceedings of ICWET 2011, ACM International Conference, Mumbai, India, Feb. 2011
  9. X. Pan, Q. Ruan, "A Modified Preprocessing Method for Palmprint Recognition", In Proceedings of 8th International Conference on Signal Processing, 2006 , IEEE DOI : 0-7803-9737-1/06
  10. K. Ito, T. Aokit, H. Nakajima, K. Kobayashi,T. Higuchi, "A Palmprint Recognition Algorithm Using Phase-Based Image Matching", In proceedings of IEEE International Conference on Image Processing, pp. 2669 - 2672, 2006
  11. N. E. Othman, A. A. Azid, S. Samad and A. Hussain, "A Palmprint Recognition System using Correlation Filters", In Proceedings of 4th Student Conference on Research and Development (SCOReD 2006), Shah Alam, Selangor, Malaysia,pp.91-94, June 2006
  12. M. Laadjel, A. Bouridane, F. Kurugollu, "EigenspectraPalmprint Recognition", Proceedings of 4th IEEE International Symposium on Electronic Design, Test & Applications, IEEE DOI: 10.1109/DELTA.2008.62, pp.382-385, 2008
  13. M. Ekinci and M. Aykut, "Gabor-based Kernel PCA for Palmprint Recognition", Electronics Letters, Vol. 43 No. 20, 27th September 2007
  14. M. You, S. Jifeng, "Palmprint Recognition Based on 2DPCA–Moment Invariant", In Proceedings of 5th International Conference on Image and Graphics 2009, IEEE: DOI 10.1109/ICIG.2009.168, pp.149-155,2009
  15. C. Wen, J. Zhang, "Palmprint Recognition based on Gabor Wavelets and 2-Dimensional PCA & PCA", In Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, Beijing, China, pp. 1518 - 1523, Nov. 2007
  16. S. Iitsuka, K. Miyazawa, T. Aoki, "A Palmprint Recognition Algorithm Using Principal Component Analysis Of Phase Information",ICIP'09 Proceedings of the 16th IEEE international conference on Image, ICIP 2009, pp.1973-1976,2009
  17. S. Iitsuka, K. Miyazawa,T. Aoki, "Palmprint Identification Using Wavelet Energy", International Conference on Intelligent and Advanced Systems 2007, pp. 714 - 719 ,2007
  18. K. Wong, G. Sainarayanan, A. Chekima, "Palmprint Identification Using Wavelet Energy", In Proceedings of International Conference on Intelligent and Advanced Systems 2007, pp.714-719, 2007
  19. X. Wu, K. Wang, D. Zhang, "Wavelet Based Palmprint Recognition", Proceedings of the First International Conference on Machine Learning and Cybernetics, Beijing, 4-5 November 2002, pp. 1256-1257,2002
  20. H B Kekre, V A Bharadi, "Palmprint Recognition Using Kekre’s Wavelet’s Energy Entropy Based Feature Vector", Proceedings of International Conference & Workshop on Emerging Trends in Technology 2011, TCET, Mumbai, India, pp. 39-45, Feb. 2011
  21. S. Attarchi, K. Faez, A. Asghari, "A Fast and Accurate Iris Recognition Method Using the Complex Inversion Map and 2DPCA", 7th IEEE/ACIS International Conference on
  22. Computer and Information Science, ICIS 08, pp. 179 - 184 ,2008
  23. Z. Zhou, H. Wu , Q. Lv,"A New Iris Recognition Method Based on Gabor Wavelet Neural Network", IIH-MSP '08 Proceedings of the 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 1101 - 1104 ,Aug. 2008
  24. H. Koh, W. Lee, M. Chun, "A Multimodal Iris Recognition Using Gabor Transform and contourlet",2nd International Conference on Signal Processing and Communication Systems, 2008, ICSPCS 2008, pp. 1 - 6,Dec. 2008
  25. C. Ching, C. Chen," High Performance Iris Recognition Based on LDA and LPCC",17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’05),pp. pp. 421-426, 2005
  26. H. F. Harmuth, “Applications of Walsh Functions in Communications." IEEE Spectrum 6, pp. 82-91, 1969
  27. E. W. Weisstein, "Walsh Function", From MathWorld-A Wolfram Web Resource, http://mathworld.wolfram.com/ WalshFunction.html
  28. H. B. Kekre, T. K. Sarode, R. Vig, "Fingerprint Matching using Sectorized Complex Walsh Plane in Transform Domain", Proceedings of ICWET 2011, ACM International Conference, Mumbai, India, Feb. 2011
  29. L. Ma, T. Tan, Y. Wang, and D. Zhang, “Efficient Iris Recognition by characterizing Key Local Variations”, IEEE Transaction on IP, Vol. 13, No.6, pp. 739-750, 2004
  30. Hong Kong University PolyUDatabase : www4.comp.polyu. edu.hk/~biometrics/2D_3D_Palmprint.htm
  31. Phoenix Iris Database: http://phoenix.inf.upol.cz/iris/ download/, (Referred on 10-09-2009, 10:00 a.m.)
  32. H. B. Kekre, V. A. Bharadi , “Palmprint Recognition Using Kekre’s Wavelet’s Energy Entropy Based Feature Vector”, ACM International Conference & Workshop on Emerging Trends in Technology 2011, India, pp.39-45, Feb. 2011
  33. H. B. Kekre, A. Athawale, D. Sadavarti, "Algorithm To Generate Kekre’s Wavelet Transform from Kekre’s Transform", IJSET, June 2010
  34. H. B. Kekre, V. A. Bharadi , “Performance Comparison of DCT, FFT, WHT, Kekre’s Transform & Gabor Filter Based Feature Vectors for On-Line Signature Recognition”, International Journal of Computer Application (IJCA), Special Issue for ACM International Conference ICWET 2011, February 2011
  35. H. B. Kekre, V. A. Bharadi, “Hybrid Multimodal Biometric Recognition Using Kekre’s Wavelets, 1D Transforms &Kekre’s Vector Quantization Algorithms Based Feature Extraction of Face & Iris”, International Journal of Computer Application (IJCA), Special Issue for ACM International Conference ICWET 2011, February 2011
Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Transforms DCT FFT Kekre Transform Hartley Transform Kekre Wavelets