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A Rotated Image Matching Method Based on CISD.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Derong Liu
Shumin Fei
Zeng-Guang Hou
Huaguang Zhang
Changyin Sun
Source :
Advances in Neural Networks: ISNN 2007 (9783540723820); 2007, p1346-1352, 7p
Publication Year :
2007

Abstract

In the image registration process, there always exists rotation transformation. The ordinary methods such as NCC (Normalized Cross Correlation Algorithm), SD (Square Difference Algorithm), SSDA (Sequential Similarity Detection Algorithm), are not suitable for rotated image registration. In this paper, a method based on circular template, intensity distribution and SD is proposed for rotation image registration. Through the CPs (Control Points) got by the proposed method, transformation model and least square method, the rotation parameters are obtained. Experimental results verify its effectiveness. Compared with the existing feature-based approaches, it is easier to obtain CPs and needs no salient objects. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540723820
Database :
Complementary Index
Journal :
Advances in Neural Networks: ISNN 2007 (9783540723820)
Publication Type :
Book
Accession number :
33176548
Full Text :
https://doi.org/10.1007/978-3-540-72383-7_157