CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Image Enhancement using Hybrid Fuzzy Inference System (IEHFS)

by Kumud Saxena, Avinash Pokhriyal, Sushma Lehri
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 60 - Number 16
Year of Publication: 2012
Authors: Kumud Saxena, Avinash Pokhriyal, Sushma Lehri
10.5120/9774-4333

Kumud Saxena, Avinash Pokhriyal, Sushma Lehri . Image Enhancement using Hybrid Fuzzy Inference System (IEHFS). International Journal of Computer Applications. 60, 16 ( December 2012), 8-13. DOI=10.5120/9774-4333

@article{ 10.5120/9774-4333,
author = { Kumud Saxena, Avinash Pokhriyal, Sushma Lehri },
title = { Image Enhancement using Hybrid Fuzzy Inference System (IEHFS) },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 60 },
number = { 16 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume60/number16/9774-4333/ },
doi = { 10.5120/9774-4333 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:07:06.703088+05:30
%A Kumud Saxena
%A Avinash Pokhriyal
%A Sushma Lehri
%T Image Enhancement using Hybrid Fuzzy Inference System (IEHFS)
%J International Journal of Computer Applications
%@ 0975-8887
%V 60
%N 16
%P 8-13
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image enhancement is a primary need for the recognition of different biometrics in biometric-based identification systems. The recognition-rate of a biometric system depends heavily upon the quality of the input biometric given to the system. In this paper, a novel hybrid Fuzzy model (IEHFS) is proposed to improve the visual quality of iris images. The experimental results based on calculating PSNR values show that this hybrid model enhances the noisy biometric images better than the conventional filters like median filter and Wiener filter.

References
  1. Gonzalez, R. C . and Woods, R. E. 2001. Digital Image Processing, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall.
  2. Bovik, A. C. , Huang, T. S. and Munson, D. C. 1983. A generalization of median filtering using linear combinations of order statistics. IEEE Transactions on Acoustics, Speech, and Signal Processing, 31(6) (December 1983),:1342-1349.
  3. Brownrigg, D. 1984. "The weighted median filter," Commun. Assoc. Comput. , (Mar. 1984) pp. 807–818.
  4. Ko, S. J. and Lee, S. J. 1991. "Center weighted median filters and their applications to image enhancement," IEEE Trans. Circuits Syst. , vol. 15, no. 9 (Sep. 1991), pp. 984–993.
  5. Kerre, E. and Nachtegael, M. Eds. 2000, Fuzzy Techniques in Image Processing. New York: Springer-Verlag, vol. 52, Studies in Fuzziness and Soft Computing.
  6. Thanh, N. M. and Chen, M. "Image Denoising Using Adaptive Neuro-Fuzzy System", IJAM_36_1_11, Feb. 2007.
  7. Russo, F. and Ramponi, G. "A fuzzy operator for the enhancement of blurred and noisy images," IEEE Trans. Image Processing, vol. 4, pp. 1169–1174, Aug. 1995.
  8. C. -S. Lee, Y. -H. Kuo, and P. -T. Yu, "Weighted fuzzy mean filters for image processing," Fuzzy Sets Syst. , no. 89, pp. 157–180, 1997.
  9. Farbiz F. and Menhaj, M. B. 2000. Fuzzy Techniques in Image Processing. New York: Springer-Verlag, vol. 52, Studies in Fuzziness and Soft Computing, ch. A fuzzy logic control based approach for image filtering, pp. 194–221.
  10. Huang, T. S. , Yang, G. J. and Tang, G. Y. 1979. "Fast Two-Dimensional Median Filtering Algorithm," IEEE Transactions on Acoustics, Speech, and Signal Processing, 1, pp. 13–18.
  11. Nodes, T. A. and Gallagher, N. C. Jr. 1984. "The Output Distribution of Median Type Filters," IEEE Transactions on Communications, COM-32.
  12. Hwang, H. and Haddad, R. A. 1995. "Adaptive median filters: new algorithms and results," IEEE Transactions on Image Processing, 4, pp. 499–502.
  13. Chen, T. and Wu, H. R. 2001. "Space variant median filters for the restoration of impulse noise corrupted images," IEEE Transactions on Circuits and Systems II, 48, pp. 784–789.
  14. H. -L. Eng and K. -K. Ma, "Noise Adaptive Soft-Switching Median Filter," IEEE Transactions on Image Processing, 10 , pp. 242–251,2001.
  15. G. Pok, J. C. Liu, and A. S. Nair, "Selective Removal of Impulse Noise Based on Lomogeneity level Information," IEEE Transactions on Image Processing, 12 , pp. 85–92,2003.
  16. Mamdani, E. H. and Assilian, S. 1975. "An experiment in linguistic synthesis with a fuzzy logic controller," International Journal of Man-Machine Studies, 7(1):1-13.
  17. Takagi,T. and Sugeno, M. "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Syst. , Man, Cybern. , vol. 15, pp. 116–132, Jan. 1985.
  18. Buckley, J. J. and Feuring, T. 1999. Fuzzy and Neural: Interactions and Applications, ser. Studies in Fuzziness and Soft Computing. Heidelberg, Germany: Physica-Verlag.
  19. Lin, C. T. and C. S. George Lee, C. S. 1996. Neural Fuzzy Systems--ANeuro-Fuzzy Synergism to Intelligent Systems. Englewood Cliffs, NJ:Prentice-Hall.
  20. J. S. R. Jang, C. T. Sun, and E. Mizutani, 1997. Neuro-Fuzzy and Soft Computing. Englewood Cliffs, NJ: Prentice-Hall.
Index Terms

Computer Science
Information Sciences

Keywords

IEHFS Wiener filter Median filter Top hat and bottom hat PSNR SSIM

Powered by PhDFocusTM