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Kolmogorov-Smirnov Test for Image Comparison

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Book cover Computational Science and Its Applications – ICCSA 2004 (ICCSA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3046))

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Abstract

We apply the Kolmogorov-Smirnov test to test whether two distributions of 256 gray intensities are the same. Thus, this test may be useful to compare unstructured images, such as microscopic images in medicine. Usually, histogram is used to show the distribution of gray level intensities. We argue that cumulative distribution function (gray distribution) may be more informative when comparing several gray images. The Kolmogorov-Smirnov test is illustrated by hystology images from untreated and treated breast cancer tumors. The test is generalized to ensembles of gray images. Limitations of the Kolmogorov-Smirnov test are discussed.

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Author information

Authors and Affiliations

  1. Dartmouth College, Hanover, NH, 03755, USA

    Eugene Demidenko

Authors
  1. Eugene Demidenko
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Editor information

Editors and Affiliations

  1. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  2. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  5. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  6. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

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© 2004 Springer-Verlag Berlin Heidelberg

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Demidenko, E. (2004). Kolmogorov-Smirnov Test for Image Comparison. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds) Computational Science and Its Applications – ICCSA 2004. ICCSA 2004. Lecture Notes in Computer Science, vol 3046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24768-5_100

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  • DOI: https://doi.org/10.1007/978-3-540-24768-5_100

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22060-2

  • Online ISBN: 978-3-540-24768-5

  • eBook Packages: Springer Book Archive

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