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Rough Entropy Hierarchical Agglomerative Clustering in Image Segmentation

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Transactions on Rough Sets XIII

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 6499))

Abstract

In data clustering there is a constant demand on development of new algorithmic schemes capable of robust and correct data handling. This demand has been additionally highly fueled and increased by emerging new technologies in data imagery area. Hierarchical clustering represents established data grouping technique with a wide spectrum of application, especially in image analysis branch. In the paper, a new algorithmic rough entropy framework has been applied in the hierarchical clustering setting. During cluster merges the quality of the resultant merges has been assessed on the base of the rough entropy. Incorporating rough entropy measure as the evaluation of cluster quality takes into account inherent uncertainty, vagueness and impreciseness. The experimental results suggest that hierarchies created during rough entropy based merging process are robust and of high quality, giving possible area for future research applications in real implementations.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Bialystok University of Technology, Wiejska 45A, 15-351, Bialystok, Poland

    Dariusz Małyszko & Jarosław Stepaniuk

Authors
  1. Dariusz Małyszko
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  2. Jarosław Stepaniuk
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

  3. Department of Computer Science, The University of Akron, 44325-4003, Akron, OH, USA

    Chien-Chung Chan

  4. Department of Electrical Engineering and Computer Science, The University of Kansas, 66045, Lawrence, KS, USA

    Jerzy W. Grzymala-Busse

  5. Department of Computer Science, University of Regina, SK S4S 0A2, Regina, Canada

    Wojciech P. Ziarko

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© 2011 Springer-Verlag Berlin Heidelberg

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Małyszko, D., Stepaniuk, J. (2011). Rough Entropy Hierarchical Agglomerative Clustering in Image Segmentation. In: Peters, J.F., Skowron, A., Chan, CC., Grzymala-Busse, J.W., Ziarko, W.P. (eds) Transactions on Rough Sets XIII. Lecture Notes in Computer Science, vol 6499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18302-7_6

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  • DOI: https://doi.org/10.1007/978-3-642-18302-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18301-0

  • Online ISBN: 978-3-642-18302-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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