Median-based image thresholding

Xue, J.H. and Titterington, D.M. (2011) Median-based image thresholding. Image and Vision Computing, 29(9), pp. 631-637. (doi:10.1016/j.imavis.2011.06.003)

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Abstract

In order to select an optimal threshold for image thresholding that is relatively robust to the presence of skew and heavy-tailed class-conditional distributions, we propose two median-based approaches: one is an extension of Otsu's method and the other is an extension of Kittler and Illingworth's minimum error thresholding. We provide theoretical interpretation of the new approaches, based on mixtures of Laplace distributions. The two extensions preserve the methodological simplicity and computational efficiency of their original methods, and in general can achieve more robust performance when the data for either class is skew and heavy-tailed. We also discuss some limitations of the new approaches.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Titterington, Professor Michael
Authors: Xue, J.H., and Titterington, D.M.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Image and Vision Computing
Publisher:Elsevier BV, North-Holland
ISSN:0262-8856
Published Online:20 June 2011

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