Abstract
This paper presents a simple and effective method for matching two uncalibrated images. First, corner points are extracted in both images separately. Then the initial set of point matches is obtained by singular value decomposition of a well-designed correspondence strength matrix. A new expression of this matrix is introduced to get more reliable initial matches. Last, the epipolar geometry constraint is imposed to reject the false matches. Experimental results on real images show this method to be effective for general image matching.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zhang, Z., Deriche, R., Faugeras, O., Luong, Q.-T.: A Robust Technique for Matching Two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry. Artificial Intelligence Journal 78, 87–119 (1995)
Pilu, M.: A direct method for stereo correspondence based on singular value decomposition. In: IEEE CVPR, pp. 261–266 (1997)
Baumberg, A.: Reliable feature matching across widely separated views. In: IEEE CVPR, pp. 774–781 (2000)
Tell, D., Carlsson, S.: Combining Appearance and Topology for Wide Baseline Matching. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 68–81. Springer, Heidelberg (2002)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Fourth Alvey Vision Conference, pp. 148–151 (1988)
Schmid, C., Mohr, R., Bauckhage, C.: Evaluation of Interest Point Detectors. International Journal of Computer Vision 37, 151–172 (2000)
Scott, G., Longuet-Higgins, H.: An algorithm for associating the features of two patterns. In: Proceedings of the Royal Statistical Society of London, vol. B244, pp. 21–26 (1991)
Xu, G., Nishimura, E., Tsuji, S.: Image correspondence and segmentation by epipolar lines: Theory, algorithm and applications. Technical report, Dept. of Systems Engineering, Osaka University, Japan (1993)
Pollard, S.B., Mayhew, J.E.W., Frisby, J.P.: PMF: A stereo correspondence algorithm using a disparity gradient limit. Perception 14, 449–470 (1985)
Faustner, W.: A feature based correspondence algorithm for image matching. International Archives of Photogrammetry and Remote Sensing 26, 150–166 (1986)
Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM 24, 381–395 (1981)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhao, F. (2004). Image Matching Based on Singular Value Decomposition. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30543-9_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-30543-9_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23985-7
Online ISBN: 978-3-540-30543-9
eBook Packages: Computer ScienceComputer Science (R0)