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Two-stage formation of a spatial transformation for image matching
Ye.V. Goshin, A.P. Kotov, V.A. Fursov
Image Processing Systems Institute, Russian Academy of Sciences,
Samara State Aerospace University
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Full text of article: Russian language.
DOI: 10.18287/0134-2452-2014-38-4-886-891
Pages: 886-891.
Abstract:
In this paper a problem of image matching is considered. We consider the matching of images, which represent the same scene recorded by different sensors. In this paper we discuss problems arising when there are uninformative areas on the images, in which points matching errors occur frequently. In the proposed technology a projective transform is constructed from reliable corresponding points in an informative area. And then this transform is used to determine and adjust the corresponding points in an uninformative area. Experimental results illustrate the effectiveness of the proposed technology.
Key words:
image processing, image informativity estimation, image matching, projective transform, Delaunay triangulation, affine transform.
Citation:
Goshin YV, Kotov AP, Fursov VA. Two-stage formation of a spatial transformation for image matching. Computer Optics 2014; 38(4): 886-891. DOI: 10.18287/0134-2452-2014-38-4-886-891.
References:
- Bessmeltsev, V.P. Fast image registration algorithm for automated inspection of laser micromachining / V.P. Bessmeltsev, E.D. Bulushev // Computer Optics. – 2014. – Vol. 38(2). – P. 343-350. – ISSN 0134-2452.
- Myasnikov, V.V. Method for detection of vehicles in digital aerial and space remote sensed images / V.V. Myasnikov // Computer Optics. – 2012. – Vol. 36(3). – P. 429-438. – ISSN 0134-2452.
- Ilyasova, N.Y. Computer technology for the spatial reconstruction of the coronary vesels structure from angigographic projections / N.Y. Ilyasova, N.L. Kazansky, A.O. Korepanov, A.V. Kupriyanov, A.V. Ustinov, A.G. Khramov // Computer Optics. – 2009. – Vol. 33(3). – P. 281-317. – ISSN 0134-2452. – (In Russian).
- Crum, W.R. Non-rigid image registration: theory and practice / W.R. Crum, T. Hartkens, D.L.G. Hill // The British Journal of Radiology. – 2014. – Vol. 77. – P. 140-153.
- Chui, H. A new point matching algorithm for non-rigid registration / H. Chui, A. Rangarajan // Computer Vision and Image Understanding. – 2003. – Vol. 89, Issue 2. – P. 114-141.
- Loeckx, D. Nonrigid image registration using free-form deformations with a local rigidity constraint / D. Loeckx, F. Maes, D. Vandermeulen, P. Suetens // Medical Image Computing and Computer-Assisted Intervention–MICCAI 2004. – Springer Berlin Heidelberg, 2004. – P. 639-646.
- Ke, Y. PCA-SIFT: A more distinctive representation for local image descriptors / Y. Ke, R. Sukthankar // Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on. – IEEE, 2004. – Vol. 2. – P. 506- 513.
- Bay, H. Surf: Speeded up robust features / H. Bay, T. Tuytelaars, L. Van Gool // Computer Vision–ECCV 2006. – Springer Berlin Heidelberg, – 2006. – P. 404-417.
- Pratt, W. Digital Image Processing. – 4th ed. – Wiley, 2007.
- Raguram, R. A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus / R. Raguram, J.M. Frahm, M. Pollefeys // Computer Vision–ECCV 2008. – Springer Berlin Heidelberg, 2008. – P. 500-513.
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