Volume 9 Number 4 (Apr. 2014)
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JSW 2014 Vol.9(4): 964-969 ISSN: 1796-217X
doi: 10.4304/jsw.9.4.964-969

A Method of Image Registration Based On Best Similarity of Local Geometric Figure

Zetao Jiang1, Le Zhou2, Liwen Zhang2
1Guilin Uniersity of Electronic Technology, Guilin,China Nanchang Hangkong University, Nanchang, China
2Nanchang Hangkong University, Nanchang, China

Abstract—Image Registration is an important part of computer vision. We propose a method of image registration by obtaining best similarity of local geometric figure that utilizes opposite core difference (OCD) of corresponding local figure. This method gets initial matching after describing precisely SIFT points by constructing feature subspaces based on the detection of SIFT feature points. Then we describe the corresponding similarity by OCD of local figure constructed by SIFT points and choose the feature points that possess highest similarity measure as point set to compute projective transformation matrix Topt . Experiments have proved that the precision of the matrix Topt  and the Image matching is at a high level.

Index Terms—SIFT feature subspace, local geometric similarity, projective, OCD


Cite: Zetao Jiang, Le Zhou, Liwen Zhang, "A Method of Image Registration Based On Best Similarity of Local Geometric Figure," Journal of Software vol. 9, no. 4, pp. 964-969, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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