Research on Matching Pair Purification Methods of Image Based on SIFT Algorithm

Qiang Li; Qi Yuan Sun

doi:10.4028/www.scientific.net/AMM.713-715.1851

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715Research on Matching Pair Purification Methods of...

Research on Matching Pair Purification Methods of Image Based on SIFT Algorithm

Abstract:

In view of the SIFT algorithm in image matching will produce a lot of mismatches, the paper has applied a method which is based on Hough Transform will remove the SIFT matching error effectively. Firstly, to use the SIFT algorithm finish the image matching roughly. And then, using the Hough Transform to form the equal division hough units. And according to the matching parameter to distribute all the match into the hough units. The match in the units which has least matching-pair will be deleted. Experimental results show that the method can effectively improve the matching accuracy of feature matching and it lays a foundation for the following robot vision navigation.

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Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

1851-1854

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.1851

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Online since:

January 2015

Authors:

Qiang Li*, Qi Yuan Sun

Keywords:

Hough Transform, Matching Purification, SIFT Algorithm

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* - Corresponding Author

References

[1] Li qi. The image matching algorithm based on wavelet transform hardware design and implementation [D]. Harbin: Harbin industrial university, (2012).

Google Scholar

[2] Arvin. Image matching algorithm based on SIFT feature points [D]. Wuhan: huazhong university of science and technology, (2013).

Google Scholar

[3] Yong-ming Wang, Gui-jin Wang. Local invariant features and image description [M]. Beijing: national defence industry press, (2010).

Google Scholar

[4] LOWE D G. Distinctive image features from scale-invariant key-points[J]. International Journal of Computer Vision, 2004, 60(2): 91-110.

DOI: 10.1023/b:visi.0000029664.99615.94

Google Scholar

[5] Da-long Gu, Luan Zeng. The image matching algorithm based on SURF improvement [J]. Journal of modern electronic technology, 2012, 35 (14) : 79-83.

Google Scholar

[6] KUGLIN C D, HINES D C. The Phase Correlation Image Alignment method[J]. IEEE Conference on Cybernetics and Society, 1975: 163-165.

Google Scholar