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Statistical behavior of edge detectors

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Abstract

In this paper we present a method for estimating the statistical properties of two well-known edge detectors: the non maxima suppression and the zero crossing of the Laplacian algorithms. Assuming the data are corrupted by an additive Gaussian noise we derive the probability density function (pdf) of the detected edge. Thanks to this approach the computed pdf explicitly depends on the parameters of the edge detector. Experimental results on real images and comparisons with Monte Carlo simulations are presented in order to characterize the performance of this method.

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Authors and Affiliations

  1. UMR CNRS 6168 LSIS, Université du Sud Toulon-Var, BP 20132, 83957, La Garde Cedex, France

    Frédéric Bouchara

  2. EA 2991 EDM, Université de Montpellier I, 34090, Montpellier, France

    Sofiane Ramdani

Authors
  1. Frédéric Bouchara
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  2. Sofiane Ramdani
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Correspondence to Frédéric Bouchara.

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Bouchara, F., Ramdani, S. Statistical behavior of edge detectors. SIViP 1, 273–285 (2007). https://doi.org/10.1007/s11760-007-0024-5

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  • DOI: https://doi.org/10.1007/s11760-007-0024-5

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