Abstract
The paper presents a new approach to image matching based on the developed adaptive window growing algorithm. This integer-only algorithm operates on monochrome images transformed into the Census nonparametric representation. It effectively computes the entropy of the local areas and adjusts their size if the entropy is not sufficient. This way the method allows for avoidance of featureless areas that cannot be reliably matched, at the same time maintaining the matching window as small as possible. The special stress has been also laid on efficient implementation that can fit the custom hardware architectures. Therefore the presented algorithm requires only an integer arithmetic. Many experiments with the presented technique applied to the stereovision matching showed its robustness and competing execution times.
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References
Banks, J., Bennamoun, M., Corke, P.: Non-Parametric Techniques for Fast and Robust Stereo Matching. CSIRO Manufacturing Science and Technology, Australia (1997)
Chen, Y.-S., Hung, Y.-P., Fuh, C.-S.: Fast Block Matching Algorithm Based on the Winner- Update Strategy. IEEE Trans. On Image Processing 10(8), 1212–1222 (2001)
Cyganek, B., Borgosz, J.: Maximum Disparity Threshold Estimation for Stereo Imaging Systems via Variogram Analysis. In: ICCS 2003, Russia/Australia, pp. 591–600 (2003)
Cyganek, B.: Comparison of Nonparametric Transformations and Bit Vector Matching for Stereo Correlation. In: Klette, R., Žunić, J. (eds.) IWCIA 2004. LNCS, vol. 3322, pp. 534–547. Springer, Heidelberg (2004)
Fusiello, A., et al.: Efficient stereo with multiple windowing. In: CVPR, pp. 858–863 (1997)
Haykin, S.: Neural Networks. A Comprehensive Foundation. Prentice-Hall, Englewood Cliffs (1999)
Kanade, T., Okutomi, M.: A stereo matching algorithm with an adaptive window: Theory and experiment. PAMI 16(9), 920–932 (1994)
Lotti, J.-L., Giraudon, G.: Adaptive Window Algorithm for Aerial Image Stereo. INRIA Technical Report No. 2121 (1993)
Scharstein, D., Szeliski, R.: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. IJCV 47,l (1-3), 7–42 (2002)
Veksler, O.: Fast Variable Window for Stereo Correspondence using Integral Images. In: Computer Vision and Pattern Recognition (2003)
Zabih, R., Woodfill, J.: Non-Parametric Local Transforms for Computing Visual Correspondence. In: Proc. Third European Conf. Computer Vision, pp. 150–158 (1994)
Zhengping, J.: On the Mutli-Scale Iconic Representation for Low-Level Computer Vision. Ph.D. Thesis. The Turing Institute and University of Strathclyde, 114–118 (1988)
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Cyganek, B. (2005). Adaptive Window Growing Technique for Efficient Image Matching. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492429_38
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DOI: https://doi.org/10.1007/11492429_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26153-7
Online ISBN: 978-3-540-32237-5
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