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Dissimilarity criteria and their comparison for quantitative evaluation of image segmentation: application to human retina vessels

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Abstract

The quantitative evaluation of image segmentation is an important and difficult task that is required for making a decision on the choice of a segmentation method and for the optimal tuning of its parameter values. To perform this quantitative evaluation, dissimilarity criteria are relevant with respect to the human visual perception, contrary to metrics that have been shown to be visually not adapted. This article proposes to compare eleven dissimilarity criteria together. The field of retina vessels image segmentation is taken as an application issue to emphasize the comparison of five specific image segmentation methods, with regard to their degrees of consistency and discriminancy. The DRIVE and STARE databases of retina images are employed and the manual/visual segmentations are used as a reference and as a control method. The so-called \(\epsilon \) criterion gives results in agreement with perceptually based criterions for achieving the quantitative comparison.

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Authors and Affiliations

  1. École Nationale Supérieure des Mines de Saint-Etienne, Saint–Étienne cedex, France

    Yann Gavet, Johan Debayle & Jean-Charles Pinoli

  2. LGF UMR CNRS 5307, 158 Cours Fauriel, 42023 , Saint–Étienne cedex, France

    Yann Gavet, Mathieu Fernandes, Johan Debayle & Jean-Charles Pinoli

  3. CYTOO SA, Grenoble, France

    Mathieu Fernandes

Authors
  1. Yann Gavet
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  2. Mathieu Fernandes
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  3. Johan Debayle
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  4. Jean-Charles Pinoli
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Correspondence to Yann Gavet.

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Gavet, Y., Fernandes, M., Debayle, J. et al. Dissimilarity criteria and their comparison for quantitative evaluation of image segmentation: application to human retina vessels. Machine Vision and Applications 25, 1953–1966 (2014). https://doi.org/10.1007/s00138-014-0625-2

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  • DOI: https://doi.org/10.1007/s00138-014-0625-2

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