Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/82044
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Type: Journal article
Title: Robust image matching algorithm using SIFT on multiple layered strategies
Author: Chen, Y.
Shang, L.
Hu, E.
Citation: Mathematical Problems in Engineering, 2013; 2013:452604-1-452604-12
Publisher: Gordon Breach Sci Publ Ltd
Issue Date: 2013
ISSN: 1024-123X
1563-5147
Statement of
Responsibility: 
Yong Chen, Lei Shang and Eric Hu
Abstract: As for the unsatisfactory accuracy caused by SIFT (scale-invariant feature transform) in complicated image matching, a novel matching method on multiple layered strategies is proposed in this paper. Firstly, the coarse data sets are filtered by Euclidean distance. Next, geometric feature consistency constraint is adopted to refine the corresponding feature points, discarding the points with uncoordinated slope values. Thirdly, scale and orientation clustering constraint method is proposed to precisely choose the matching points. The scale and orientation differences are employed as the elements of -means clustering in the method. Thus, two sets of feature points and the refined data set are obtained. Finally, 3 * delta rule of the refined data set is used to search all the remaining points. Our multiple layered strategies make full use of feature constraint rules to improve the matching accuracy of SIFT algorithm. The proposed matching method is compared to the traditional SIFT descriptor in various tests. The experimental results show that the proposed method outperforms the traditional SIFT algorithm with respect to correction ratio and repeatability.
Rights: Copyright © 2013 Yong Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
RMID: 0020134412
DOI: 10.1155/2013/452604
Appears in Collections:Mechanical Engineering publications

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