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The Redundancy Pyramid and Its Application to Segmentation on an Image Sequence

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Book cover Pattern Recognition (DAGM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3175))

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Abstract

Irregular pyramids organize a sequence of partitions of images in such a way that each partition is deduced from the preceding one by union of some of its regions. In this paper, we show how a single pyramid can be used to encode redundant subparts of different partitions. We obtain a pyramid that accounts for the redundancy of the partitions. This structure, naturally called the redundancy pyramid, can be used for many purposes. We also demonstrate and discuss some applications for studying image sequences.

This work was supported by the Austrian Science Foundation (FWF) under grants P14445-MAT, P14662-INF and S91 03-N04.

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References

  1. Brun, L., Kropatsch, W.G.: Construction of combinatorial pyramids. In: Proceedings of the 4th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition, pp. 1–12 (2003)

    Google Scholar 

  2. Cho, K., Meer, P.: Image segmentation from consensus information. Computer Vision and Image Understanding 68(1), 72–89 (1997)

    Article  Google Scholar 

  3. Förstner, W.: Generic estimation procedures for orientation with minimum redundant information. 2nd Course on Digital Photogrammetry (1999)

    Google Scholar 

  4. Keselman, Y., Dickinson, S.: Generic model abstraction from examples. In: Proc. IEEE Conference CVPR, December 2001, vol. 1, pp. 856–863 (2001)

    Google Scholar 

  5. Kropatsch, W.G.: Abstraction Pyramids on Discrete Representations. In: Braquelaire, A., Lachaud, J.-O., Vialard, A. (eds.) DGCI 2002. LNCS, vol. 2301, pp. 1–21. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  6. Marchadier, J., Michelin, S., Arquès, D.: Thinning GrayscaleWell-Composed Images. Pattern Recognition Letters 25, 581–590 (2004)

    Article  Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Marchadier, J., Kropatsch, W.G., Hanbury, A. (2004). The Redundancy Pyramid and Its Application to Segmentation on an Image Sequence. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28649-3_53

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  • DOI: https://doi.org/10.1007/978-3-540-28649-3_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22945-2

  • Online ISBN: 978-3-540-28649-3

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