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Quantitative Analysis of Similarity Measures of Distributions

Eric Bazan
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Petr Dokládal
Eva Dokladalova


The Earth Mover's Distance (EMD) is a metric based on the theory of optimal transport that has interesting geometrical properties for distributions comparison. However, the use of this measure is limited in comparison with other similarity measures as the Kullback-Leibler divergence. The main reason was, until recently, the computation complexity. In this paper, we present a comparative study of the dissimilarity measures most used in the literature for the comparison of distributions through a color-based image classification system and other simple examples with synthetic data. We show that today the EMD is a computa-tionally efficient measure that better reflects the similarity between two distributions.
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hal-01984970 , version 1 (17-01-2019)


  • HAL Id : hal-01984970 , version 1


Eric Bazan, Petr Dokládal, Eva Dokladalova. Quantitative Analysis of Similarity Measures of Distributions. British Machine Vision Conference 2019, BMVC 2019, Sep 2019, Cardiff, United Kingdom. ⟨hal-01984970⟩


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