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Optical Engineering

Threshold selection using a minimal histogram entropy difference
Author(s): P. K. Sahoo; Dick W. Slaaf; Thomas A. Albert
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Paper Abstract

A new gray-level threshold selection method for image segmentation is presented. It is based on minimizing the difference between entropies of the object and the background distributions of the gray-level histogram. The proposed method is similar to the maximum entropy method proposed by Kapur et al. (1985), however, the new method provided a good threshold value in many instances where the previous method did not. The effectiveness of our method is demonstrated by its performance on videomicroscopic images of the rat lung. Extension of the method to higher order probability density functions is described.

Paper Details

Date Published: 1 July 1997
PDF: 6 pages
Opt. Eng. 36(7) doi: 10.1117/1.601404
Published in: Optical Engineering Volume 36, Issue 7
Show Author Affiliations
P. K. Sahoo, Univ. of Louisville (United States)
Dick W. Slaaf, Univ. of Limburg (Netherlands)
Thomas A. Albert, Univ. of Louisville (United States)

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