Robust threshold estimation for images with unimodal histograms

Authors:
Nicolas Coudray;Jean-Luc Buessler;Jean-Philippe Urban
Affiliations:
Université de Haute-Alsace, Laboratoire MIPS, 4 Rue des Frères Lumière, 68093 Mulhouse, France;Université de Haute-Alsace, Laboratoire MIPS, 4 Rue des Frères Lumière, 68093 Mulhouse, France;Université de Haute-Alsace, Laboratoire MIPS, 4 Rue des Frères Lumière, 68093 Mulhouse, France
Venue:
Pattern Recognition Letters
Year:
2010

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Abstract

This article introduces a method to determine in a robust manner the threshold in highly noisy gradient images. To enhance the robustness, the proposed technique is based on a piecewise linear regression to fit the whole descending slope of the histogram, rather than the search of some specific points. The algorithm gives a reliable estimation of the threshold, and is practically insensitive to the noise distribution, to the quantity of edge pixels to segment, and to random histogram fluctuations.