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A Comparison of Spatial Pattern Spectra

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Mathematical Morphology and Its Application to Signal and Image Processing (ISMM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5720))

Abstract

Pattern spectra have frequently been used in image analysis. A drawback is that they are not sensitive to changes in spatial distribution of features. Various methods have been proposed to address this problem. In this paper we compare several of these on both texture classification and image retrieval. Results show that Size Density Spectra are most versatile, and least sensitive to parameter settings.

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Authors and Affiliations

  1. Institute for Mathematics and Computing Science, University of Groningen, P.O. Box 407, 9700, AK, Groningen, The Netherlands

    Sander Land & Michael H. F. Wilkinson

Authors
  1. Sander Land
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  2. Michael H. F. Wilkinson
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Editors and Affiliations

  1. Institute of Mathematics and Computing Science, University of Groningen, P. O. Box 407, 9700, Groningen, AK, The Netherlands

    Michael H. F. Wilkinson

  2. Institute for Mathematics and Computing Science, University of Groningen, P.O. Box 800, 9700, Groningen, AK, The Netherlands

    Jos B. T. M. Roerdink

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© 2009 Springer-Verlag Berlin Heidelberg

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Land, S., Wilkinson, M.H.F. (2009). A Comparison of Spatial Pattern Spectra. In: Wilkinson, M.H.F., Roerdink, J.B.T.M. (eds) Mathematical Morphology and Its Application to Signal and Image Processing. ISMM 2009. Lecture Notes in Computer Science, vol 5720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03613-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-03613-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03612-5

  • Online ISBN: 978-3-642-03613-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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