Affine Image Registration Based on Geometric Inference

Article Preview

Abstract:

Image registration is widely used in applications for mapping one image to another. As it is often formulated as a point matching problem, in this paper, a novel method, called the Geometric Inference (GI) algorithm, is proposed for feature point based image registration. Firstly, according to affine distance invariant, the global geometric relationship between collinear correspondences is deduced and used for collinear point matching. Secondly, utilizing affine area invariant, geometric relationship between noncollinear correspondences is inferred and used for noncollinear point matching. Finally, the best affine transformation can be discovered from the correspondences composed of the collinear and noncollinear corresponding point pairs. Experiments on synthesized and real data demonstrate that GI is well-adapt to image registration as it is fast and robust to missing points, outliers, and noise.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1610-1613

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] F. Meskine, M. C Mezouar, N. A . Taleb. Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms [J]. Sensors, 10, (2010).

DOI: 10.3390/s100908553

Google Scholar

[2] W. Pan, K. Qin, Y. Chen. An adaptable-multilayer fractional fourier transform approach for image registration[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence. 31, 3 (2009).

DOI: 10.1109/tpami.2008.83

Google Scholar

[3] C. Xing, P. H. Qiu. Intensity based image registration by nonparametric local smoothing[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 33, 10, (2011).

DOI: 10.1109/tpami.2011.26

Google Scholar

[4] H. Q Bian, J. B. Su. Feature matching based on geometric constraints in weakly calibrated stereo views of curved scenes[J]. Journal of Systems Engineering and Electronics. 19, 3 , (2008).

DOI: 10.1016/s1004-4132(08)60121-8

Google Scholar

[5] J. Zhang. A study on automated image registration based on straight line features[C]. Urban Remote Sensing Joint Event, Shanghai, China. (2009).

DOI: 10.1109/urs.2009.5137503

Google Scholar

[6] M. Xia, B. Liu. Image registration by super-curves, [J]. IEEE Transaction on Image Processing. 13, 5, (2004).

Google Scholar

[7] W. L. Xu, L. H. Zhang. A geometric reasoning based algorithm for point pattern matching[J]. Science In China (F). 44, 6, (2001).

Google Scholar

[8] Y. Lamdan, J. T. Schwatrz, H. J. Wolfson. Affine invariant model-based object recognition[J]. IEEE Transaction on Robotics and Automat., 6, 5, (1990).

DOI: 10.1109/70.62047

Google Scholar