1 July 1997 Threshold selection using a minimal histogram entropy difference
P. K. Sahoo, Dick W. Slaaf, Thomas A. Albert
Author Affiliations +
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.
P. K. Sahoo, Dick W. Slaaf, and Thomas A. Albert "Threshold selection using a minimal histogram entropy difference," Optical Engineering 36(7), (1 July 1997). https://doi.org/10.1117/1.601404
Published: 1 July 1997
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Cited by 50 scholarly publications and 17 patents.
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KEYWORDS
Image segmentation

Lung

Optical engineering

Binary data

Feature extraction

Image enhancement

Digital imaging

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