Paper title:

Template Matching of Colored Image Based on Quaternion Fourier Transform and Image Pyramid Techniques

DOI: https://doi.org/10.4316/JACSM.201601005
Published in: Issue 1, (Vol. 10) / 2016
Publishing date: 2016-04-14
Pages: 30-35
Author(s): KHALIL M.I.
Abstract. Abstract–Template matching method is one of the most significant object recognition techniques and it has many applications in the field of digital signal processing and image processing and it is the base for object tracking in computer vision field. The traditional template matching by correlation is performed between gray template image w and the candidate gray image f where the template’s position is to be determined in the candidate image. This task can be achieved by measuring the similarity between the template image and the candidate image to identify and localize the existence of object instances within an image. When applying this method to colored image, the image must be converted to a gray one or decomposed to its RGB components to be processed separately. The current paper aims to apply the template matching technique to colored images via generating the quaternion Fourier transforms of both the template and candidate colored image and hence performing the cross-correlation between those transforms. Moreover, this approach is improved by representing both the image and template as pyramid multi-resolution format to reduce the time of processing. The proposed algorithm is implemented and applied to different images and templates using Matlab functions.
Keywords: Matching By Cross-correlation, Digital Signal Processing, Image Processing, Quaternion Fourier Transform, Image Pyramid
References:

1. J. P. Lewis, “Fast normalized cross correlation, industrial light and magic”, http://www.academia.edu/653962/Fast_template_matching

2. M. I. Khalil, “Car plate recognition using the template matching method,” International Journal of Computer Theory and Engineering, vol. 2, no. 5, pp. 683-687, Oct. 2010.

3. Fast Block Matching with Normalized Cross-Correlation using Walsh Transforms, TRITA-NA-P02/11, ISRN KTH/NA/P--02/11--SE, CVAP-268.

4. Jianwen and Elias E.Konofagou, “A fast normalized cross-correlation calculation method for motion estimation”, IEEE trans Ultrason Ferrolectr Freq Control, Jun 2010, 57(6), 1347-1357.

5. Khalil, M. I. "Accelerating Cross-correlation Applications via Parallel Computing." International Journal of Image, Graphics and Signal Processing (IJIGSP) 5.12 (2013): 26.

6. Kaie Briechele and Uwe D. Hanebeck, “Template matching using fast normalized cross correlation”, http://i81pc23.itec.uni-karlsruhe.de/Publikationen/SPIE01_BriechleHanebeck_CrossCorr.pdf

7. Linzer, E., Tiwari, P., Zubair, M., High Performance Algorithms for MPEG Motion Estimation, Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, 1996, pp 1934-7.

8. O. Abusaeeda, J. Evans, D. D., and J. Chan, “View synthesis of KDEX imagery for 3D security X-ray imaging,” in Proc. 4th International Conference on Imaging for Crime Detection and Prevention (ICDP-2011), 2011.

9. Ja-Han Chang, S.C.P., Ding, J.J., "2d quaternion fourier spectral analysis and its applications", IEEE International Symposium on Circuits and Systems, 2004, Vol. 3, pp. 241–244.

10. Sangwine, S., Ell, T.A., "Hypercomplex Fourier Transforms of Color Images", IEEE International Conference on Image Processing (ICIP), 2001, Vol. 1, pp. 137–140.

11. Bihan, N.L., Sangwine, S.J., "Quaternion principal component analysis of color images", IEEE International Conference on Image Processing, 2003, Vol, 1, pp. 809–812.

12. Ell T.A., "Quaternion-Fourier transforms for analysis of two-dimensional linear time-invariant partial differential systems," in Proc. 32nd Con. Decision Contr., Dec. 1993, pp. 1830-1841.

13. M.I.Khalil, Applying Quaternion Fourier Transforms for Enhancing Color Images, I.J. Image, Graphics and Signal Processing, 2012, 2, 9-15.,1793-8201

14. Joan Ogden, Edward Adelson, James Bergen, and Peter Burt. Pyramid-based computer graphics. RCA Engineer, 30(5):4–15, 1985.

15. Christian Tenllado, Roberto Lario, Manuel Prieto, and Francisco Tirado. The 2d discrete wavelet transform on programmable graphics hardware. In IASTED Visualization, Imaging and Image Processing Conference, 2004.

16. BURT, P. J., AND ADELSON, E. H. 1983. The Laplacian pyramid as a compact image code. IEEE Transactions on Communication 31, 4, 532–540

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