A Multi-Scale Image Matching Recognition Algorithm Based on Phase Correlation

Yong Gang Tian; Min Gang Wang; Ying Ping Fan

doi:10.4028/www.scientific.net/AMR.301-303.1438

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 301-303A Multi-Scale Image Matching Recognition Algorithm...

A Multi-Scale Image Matching Recognition Algorithm Based on Phase Correlation

Abstract:

The image matching recognition method of phase correlation is based on the shift characteristics of the Fourier transform. The traditional image matching recognition algorithm has significant influence of the template size upon its matching accuracy and has weak resilience to noises except for the gauss noise. Addressing these shortcomings, we proposed a multi-scale matching recognition method based on phase correlation, combined with wavelet transform and edge detection. The algorithm, processed the reference image and the template image in different scales with such steps: decomposition, denoising, reconstruction, edge detection and the Fourier transform, phase correlation. Hence, it overcome the dependence upon template size effectively and improve the reliability and the resilience of various noises. Finally, we verified the algorithm with a real ground shooting image as the reference image and an intercepted part as the template image. The results have shown that the proposed approach is better than the traditional image matching method.

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Periodical:

Advanced Materials Research (Volumes 301-303)

Pages:

1438-1443

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.301-303.1438

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Online since:

July 2011

Authors:

Yong Gang Tian, Min Gang Wang, Ying Ping Fan

Keywords:

Image Matching Recognition, Phase Correlation, Wavelet Transform (WT)

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References

[1] Zitove B, Flusser J. Image registration methods : a survey [J].

Google Scholar

[2] M. D. C. Kuglin C. D, The Phase Correlation Image Alignment Method . IEEE International Conference on Cybernetics and Society [J]. 1975, 9: pp.163-165.

Google Scholar

[3] Cheng Peiqing. Digital Signal Processing Tutorial [M]. Tsinghua University Press. 2001. 08.

Google Scholar

[4] Cheng Zengxing Yang Shouzhi wavelet transform analysis theory, algorithms, development and application [M]. National Defence Industry Press.

Google Scholar

[5] Gonzales waited, digital image processing [M], the china Ruan Yuzhi etc translation, Publishing House of Electronics Industry, (2003).

Google Scholar

[6] Li Zhoucheng etc intelligent image processing technology [M] Electronic Industry Press, (2004).

Google Scholar

[7] E. De Castro and C. Morandi. Registration of translated and rotated images using finite Fourier transforms[J]. IEEE trans. patten anal mach intellg. 9(5): 700-703, (1987).

DOI: 10.1109/tpami.1987.4767966

Google Scholar