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

Empirical Analysis of Rotation Invariance in Moment Coefficients

by Sukhjeet K. Ranade, Supriya Anand
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 15
Year of Publication: 2015
Authors: Sukhjeet K. Ranade, Supriya Anand
10.5120/21143-4198

Sukhjeet K. Ranade, Supriya Anand . Empirical Analysis of Rotation Invariance in Moment Coefficients. International Journal of Computer Applications. 119, 15 ( June 2015), 19-26. DOI=10.5120/21143-4198

@article{ 10.5120/21143-4198,
author = { Sukhjeet K. Ranade, Supriya Anand },
title = { Empirical Analysis of Rotation Invariance in Moment Coefficients },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 15 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number15/21143-4198/ },
doi = { 10.5120/21143-4198 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:04:07.819447+05:30
%A Sukhjeet K. Ranade
%A Supriya Anand
%T Empirical Analysis of Rotation Invariance in Moment Coefficients
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 15
%P 19-26
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Moments can be viewed as powerful image descriptors that capture global characteristics of an image. The magnitude of the moment coefficients is said to be invariant under geometrical transformations like rotation which makes them suitable for most of the recognition applications. But in practice, the invariance of moment coefficients is compromised due to the errors in computation. This paper presents an empirical study of some popularly used moment functions to find out the robust coefficients under rotation. The selected robust coefficients are used in face recognition under in–plane rotation. Experimental results demonstrate that the performance of the proposed method comes at par with the performance of the traditional method by using lesser number of moment coefficients and thus results in significant saving in the feature extraction time.

References
  1. M. K. Hu, "Visual Pattern Recognition by Moment Invariants," IRE transaction on Information Theory, vol. 8, pp. 179-187, 1962.
  2. M. R. Teague, "Image analysis via general theory of moments," Journal of Optical Society of America, vol. 70, no. 8, pp. 920-30, 1980.
  3. A. Broumandnia and J. Shanbehzadeh, "Fast Zernike wavelet moments for Farsi character recognition," Image and Vision Computing, vol. 25, pp. 717-726, 2007.
  4. H. S. Kim and H. K. Lee, "Invariant Image Watermark Using Zernike Moments," IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 8, pp. 766-775, 2003.
  5. N. Singhal, Y. Y. Lee, C. S. Kim and S. U. Lee, "Robust image watermarking using local Zernike moments," J. Vis. Commun. Image R. , vol. 20, pp. 408-419, 2009.
  6. C. Singh and Pooja, "Improving image retrieval using combined features of Hough transform and Zernike moments," Optics and Lasers in Engineering, vol. 49, pp. 1384-1396, 2011.
  7. D. G. Sima, H. K. Kimb and R. H. Park, "Invariant texture retrieval using modified Zernike moments," Image and Vision Computing, vol. 22, pp. 331-342, 2004.
  8. S. Farokhia, S. M. Shamsuddin, U. Sheikhb, J. Flusser, M. Khansarid and K. Jafari-Khouzani, "Near infrared face recognition by combining Zernike moments and undecimated discrete wavelet transform," Digital Signal Processing, vol. 31, pp. 13-27, 2014.
  9. S. X. Liao, "Image Analysis by Moments,Ph. D. Thesis," University of Manitoba, Winnipeg, Manitoba,Canada, 1993.
  10. A. Bhatia and E. Wolf, " On the circle polynomials of Zernike and related orthogonal sets," Mathematical Proceedings of the Cambridge Philosophical Society, vol. 50, pp. 40-48, 1954.
  11. Y. H. Pang, A. B. Teoh and D. C. Ngo, "A Discriminant Pseudo Zernike Moments in Face Recognition," Journal of Research and Practice in Information Technology, vol. 38, no. 2, pp. 197-211, 2006.
  12. R. Bailey and M. Srinath, "Orthogonal moment features for use with parametric and non-parametric classifiers," IEEETrans. PatternAnal. Mach. Intell. , vol. 18, no. 4, p. 389–399, 1996.
  13. X. Y. Wang, Y. J. Yu and H. Y. Yang, "An effective image retrieval scheme using color,texture and shape features," Comput. Stand. Interfaces, vol. 33, no. 1, p. 59–68, 2011.
  14. Y. Xin, S. Liao and M. Pawlak, "Geometrically robust image watermark via pseudo-Zernike moments," in IEEE Canadian Conference on Electrical and Computer Engineering(CCECE), Canada, 2004.
  15. Y. Pang, T. Andrew, N. David and F. Hiew, "Palmprint verifications with moments,," Journal ofWSCG, vol. 12, pp. 1-3, 2003.
  16. X. Wang, T. Ma and P. Niu, "A pseudo-Zernike moment based audio watermarking scheme robust against desynchronization attacks," Comput. Electr. Eng. , vol. 37, p. 425–443, 2011.
  17. Y. Sheng and L. Shen, "Orthogonal Fourier-Mellin moments for invariant pattern recognition," Journal of Optical Society of America. , vol. 11, no. 6, pp. 1748-1757, 1994.
  18. H. Zhang, H. Shu, P. Haigron, B. Li and L. Luo, "Construction of a complete set of orthogonal Fourier–Mellin moment invariants for pattern recognition applications," Image and Vision Computing, vol. 28 , p. 38–44, 2010 .
  19. C. Kan and M. D. Srinath, "Invariant character recognition with Zernike and orthogonal Fourier-Mellin moments," Pattern Recognition, vol. 35, pp. 143-154, 2002.
  20. T. Bin, A. Lei, C. Jiwen, K. Wenjing and L. Dandan, "Subpixel edge location based on orthogonal Fourier–Mellin moments," Image and Vision Computing, vol. 26, pp. 563-569, 2008.
  21. Y. M. Chen and J. -H. Chiang, "Face recognition using combined multiple feature extraction based on Fourier-Mellin approach for single example image per person," Pattern Recognition Letters, vol. 31, p. 1833–1841, 2010.
  22. G. Papakostas, B. Mertzios and D. Karras, "Performance of the orthogonal moments in reconstructing biomedical images," in Systems,signals and image processing IWSSIP. 16th conference on, Chalkida, Greece, 2009.
  23. H. Ren, Z. Ping, W. Bo, W. Wu and Y. Sheng, "Multidistortion-invariant image recognition with radial harmonic Fourier moments. ," Journal of Optical Society of America, vol. 20, no. 4, pp. 631-637, 2003.
  24. C. Singh and S. K. Ranade, "A high capacity image adaptive watermarking scheme with radial harmonicFourier moments," Digital Signal Processing, vol. 23, p. 1470–1482, 2013.
  25. Y. Hong-Yinga, W. Xiang-Yanga, W. Peia and Pan-Pana, "Geometrically resilient digital watermarking scheme based on radialharmonic Fourier moments magnitude," International Journal of Electronics and Communications, vol. 69, p. 389–399, 2015.
  26. W. Xiang-yang, W. Y. Li, H. Y. ,. N. Pan-pan and L. Yong-wei, "Invariant quaternion radial harmonic Fourier moments for color image retrieval," Optics & Laser Technology, vol. 66, p. 78–88, 2015.
  27. H. Ren, A. Liu, J. Zou, D. Bai and Z. Ping, "Character reconstruction with Radial harmonic Fourier moments," in Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), China, 2007.
  28. H. Ren, A. Liu, J. Zou, Z. Ping and D. Bai, "Study on a novel tumor cell recognition system based on orthogonal image moments," in 7th Asian-Pacific Conference on Medical and Biological Engineering, Beijing, China, 2008.
  29. C. Singh and E. Walia, "Computation of Zernike moments in improved Polar Configuration," Image processing ,IET, vol. 3, no. 4, pp. 217-227, 2009.
  30. C. Singh, S. Pooja and R. Upneja, "On Image Reconstruction, Numerical Stability, and Invariance of Orthogonal Radial Moments and Radial Harmonic Transforms," Pattern Recognition and Image Analysis, vol. 21, no. 4, pp. 663-676, 2011.
  31. C. Singh and A. M. Sahan, "Face recognition using complex wavelet moments," Optics & Laser Technology, vol. 47, pp. 256-267, 2013.
  32. N. H. Foon, Y. H. Pang, A. T. B. Jin and D. N. C. Ling, "An efficient method for human face recognition using wavelet transform and Zernike moments. ," in Computer Graphics, Imaging and Visualization, CGIV 2004. Proceedings. International Conference on, Washington,U. S. A, 2004.
  33. C. Singh, E. Walia and N. Mittal, "Discriminative Zernike and Pseudo Zernike Moments for Face Recognition," International Journal of Computer Vision and Image Processing (IJCVIP), vol. 2, no. 2, pp. 12-35, 2012.
  34. C. Singh and A. Aggarwal, "A noise resistant image matching method using angular radial transform," Digital Signal Processing, vol. 33, p. 116–124, 2014.
  35. "The Database of Faces," AT&T Laboratories, 1994. [Online]. Available: http://www. cl. cam. ac. uk/research/dtg/attarchive/facedatabase. html. [Accessed 14 March 2015].
Index Terms

Computer Science
Information Sciences

Keywords

Zernike moments pseudo-Zernike moments Rotation invariance Face recognition.

Powered by PhDFocusTM