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Constructing Stochastic Pyramids by MIDES — Maximal Independent Directed Edge Set

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Graph Based Representations in Pattern Recognition (GbRPR 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2726))

Abstract

We present a new method (MIDES) to determine contraction kernels for the construction of graph pyramids. Experimentally the new method has a reduction factor higher than 2.0. Thus, the new method yields a higher reduction factor than the stochastic decimation algorithm (MIS) and maximal independent edge set (MIES), in all tests. This means the number of vertices in the subgraph induced by any set of contractible edges is reduced to half or less by a single parallel contraction. The lower bound of the reduction factor becomes crucial with large images.

This paper has been supported by the Austrian Science Fund under grants P14445-MAT and P14662-INF

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Author information

Authors and Affiliations

  1. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation, Vienna University of Technology, Favoritenstrasse 9, A-1040, Vienna, Austria

    Yll Haxhimusa & Walter G. Kropatsch

  2. Dipartimento di Informatica, Università di Ca’ Foscari di Venezia, Via Torino 155, 30172, Mestre (VE), Italy

    Roland Glantz

Authors
  1. Yll Haxhimusa
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  2. Roland Glantz
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  3. Walter G. Kropatsch
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of York, York, YO1 5DD, UK

    Edwin Hancock

  2. D.I.I.I.E., Università degli Studi di Salerno, Via Ponte don Melillo, 1, 84084, Fisciano (SA), Italy

    Mario Vento

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© 2003 Springer-Verlag Berlin Heidelberg

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Haxhimusa, Y., Glantz, R., Kropatsch, W.G. (2003). Constructing Stochastic Pyramids by MIDES — Maximal Independent Directed Edge Set. In: Hancock, E., Vento, M. (eds) Graph Based Representations in Pattern Recognition. GbRPR 2003. Lecture Notes in Computer Science, vol 2726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45028-9_3

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  • DOI: https://doi.org/10.1007/3-540-45028-9_3

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  • Print ISBN: 978-3-540-40452-1

  • Online ISBN: 978-3-540-45028-3

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