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Hierarchical Primitives Based Contour Matching

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Book cover Pattern Recognition (DAGM 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2449))

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Abstract

An algorithm for contour matching is presented in this paper. It is implemented in two steps: firstly, bottom-up, corners are matched, the matched corner points guide line segment matching, and then the matched line segments guide contour matching. Line segments are grouped with the signature function defined in [10] from the extracted contours of image pairs. Secondly, top-down, with the computed signature functions of the matched contours, the contour points are corresponded by modifying the initial matching from line segments. The novelty of our approach is that (1) features are incorporated, and the matching is implemented in two steps (bottom-up and top-down), thus dense correspondences along contours are acquired. Disadvantages such as the sparseness from only point correspondences, the inaccuracies from only line correspondences, and feature loss of correspondences along epipolar lines are avoided; (2) unlike the conventional way of matching along epipolar lines after rectification, signature functions developed in [10] are used to characterize the contours so that the matching is implemented along contours.

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References

  1. Image Database Carnegie-Mellon. CMU/VASC Image Database. World Wide Web, http://www.IUS.cs.cmu.edu/idb/html/motion/index.html, July, 1997. Last modified August 26, 2000.

    Google Scholar 

  2. Yuh-Lin Chang and J. K. Aggarwal. Line correspondences from cooperating spatial and temporal grouping processes for a sequence of images. In Computer Vision and Image Understanding, volume 67, No.2, 1997.

    Google Scholar 

  3. R. Deriche and O. D. Faugeras. 2d curve matching using high curvature points. In Proc. of the 10th IAPR, 1990.

    Google Scholar 

  4. Oliver Faugeras. Three-Dimensional Computer Vision, A Geometric Viewpoint. The MIT Press, 1996.

    Google Scholar 

  5. Joon Hee Han and Jong Seung Park. Contour matching using epipolar geometry. In IEEE Trans. on PAMI, volume 22, No. 4, April 2000.

    Google Scholar 

  6. C. Harris and M. Stephens. A combined corner and edge detector. In Proc. of 4th Alvey Vision Conference, 1988.

    Google Scholar 

  7. Christian Heipke. Overview of image matching techniques. In OEEPE, Workshop on the Application of Digital Photogrammetric Workstations, Lausanne, March 4–6 1996.

    Google Scholar 

  8. Jams H. McIntosh and Kathleen M. Mutch. Matching straight lines. In Computer Vision, Graphics, and Image Processing, volume 43, 1986.

    Google Scholar 

  9. S.M. Smith and J. M. Brady. Susan-a new approach to low level image processing. In Int. Journal of Computer Vision, also Technical Report TR95SMS1c, 1997.

    Google Scholar 

  10. X.-F. Zhang. Feature Based 3D Reconstruction of Man-made Scenes from Image Sequences. In Ph. D Thesis, University of Freiburg, Freiburg im Breisgau, Dec. 2001; ISBN 3-8322-0203-X, Shaker Verlag, Aachen 2002.

    Google Scholar 

  11. Z. Zhang, R. Deriche, O. Faugeras, and Q.-T. Luong. A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry. In Artificial Intelligence Journal, volume 78, October 1995. Also Technical Report No.2273, Inria Sophia-antipolis, also in Proc. 3rd Int. Conf. Automation Robotics Computer Vision, Singapore, Nov. 1994.

    Google Scholar 

  12. Zhengyou Zhang. Software Image-Matching. World Wide Web, http://www-sop.inria.fr/robotvis/personnel/zzhang/softwares.html.

    Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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Zhang, X., Burkhardt, H. (2002). Hierarchical Primitives Based Contour Matching. In: Van Gool, L. (eds) Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, vol 2449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45783-6_36

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  • DOI: https://doi.org/10.1007/3-540-45783-6_36

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44209-7

  • Online ISBN: 978-3-540-45783-1

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