Abstract
This paper presents two computationally efficient dynamic-time warping algorithms for image registration in video sequence through histogram based image segmentation. The key idea is to warp the histogram in an input frame to create an approximation of a reference frame. Any histogram based thresholding method can then be applied to create consistent regions in both the input and the approximated reference frames. Experiments of the proposed algorithm are used to demonstrate that more consistent matches can found after thresholding.
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
Brown, L.G.: A survey of image registration techniques. ACM Computing Surveys 24(4), 325–376 (1992)
Zitová, B., Flusser, J.: Image registration methods: a survey. Image Vision Comput. 21(11), 977–1000 (2003)
Maintz, J.B.A., Viergever, M.A.: A survey of medical image registration. Medical Image Analysis 2(1) (1998)
Flusser, J., Suk, T.: A Moment-based Approach to Registration of Images with affine Geometric Distortion. IEEE Trans. on Geoscience and Remote Sensing 32(2) (March 1994)
Dai, X., Khorram, S.: A feature-based image registration algorithm using improved chain-code representation combined with invariant moments. IEEE Trans. Geosci. Remote Sensing 37 (September 1999)
Goshtasby, A., Stockman, G.C., Page, C.V.: A region-based approach to digital image registration with subpixel accuracy. IEEE Trans. Geosci. Remote Sensing 24(3), 390–399 (1986)
Weszka, J.S., Nagel, R.N., Rosenfeld, A.: A threshold selection technique. IEEE Trans. Comput. C-23, 1322–1326 (1974)
Cheng, H.D., Sun, Y.: A hierarchical approach to color image segmentation using homogeneity. IEEE Trans. Image Process. 9(12), 2071–2082 (2000)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems Man Cybernet SMC-9, 62–66 (1979)
Kapur, J.N., Sahoo, P.K., Wong, A.K.C.: A New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram. Graphical Models and Image Processing 29, 273–285 (1985)
Gonçalves, H., Gonçalves, J.A., Corte-Real, L.: HAIRIS: A method for automatic image registration through histogram-based image segmentation. IEEE Trans. Image Process. 20(3), 776–789 (2011)
Chu, S., Keogh, E., Hart, D., Pazzani, M.: Iterative Deepening Dynamic Time Warping for Time Series. In: Proc. of the Second SIAM Intl. Conf. on Data Mining, Arlington, Virginia (2002)
Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM 24(6), 381–395 (1981)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Le, X., Gonzalez, R. (2013). Improving Histogram-Based Image Registration in Video Sequences through Warping. In: Huet, B., Ngo, CW., Tang, J., Zhou, ZH., Hauptmann, A.G., Yan, S. (eds) Advances in Multimedia Information Processing – PCM 2013. PCM 2013. Lecture Notes in Computer Science, vol 8294. Springer, Cham. https://doi.org/10.1007/978-3-319-03731-8_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-03731-8_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03730-1
Online ISBN: 978-3-319-03731-8
eBook Packages: Computer ScienceComputer Science (R0)