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oaioai:pure.rug.nl:publications/35918819-00b4-44bb-957e-766729988b5d

Gaussian-weighted moving-window robust automatic threshold selection

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Publication date
1 January 2003
Publisher
University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science

Abstract

A multi-scale, moving-window method for local thresholding based on Robust Automatic Threshold Selection (RATS) is developed. Using a model for the noise response of the optimal edge detector in this context, the reliability of thresholds computed at different scales is determined. The threshold computed at the smallest scale at which the reliability is suffcient is used. The performance on 2-D images is evaluated on synthetic an natural images in the presence of varying background and noise. Results show the method deals better with these problems than earlier versions of RATS at most noise levels

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ARTS repository - University of Groningen

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Last time updated on 03/06/2022

This paper was published in ARTS repository - University of Groningen.

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