Image histogram thresholding using Gaussian kernel density estimation (English)

Date
2013
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Source Title
2013 21st Signal Processing and Communications Applications Conference (SIU)
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Publisher
IEEE
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Language
Turkish
Type
Conference Paper
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Abstract

In this article, image histogram thresholding is carried out using the likelihood of a mixture of Gaussians. In the proposed approach, a prob ability density function (PDF) of the histogram is computed using Gaussian kernel density estimation in an iterative manner. The threshold is found by iteratively computing a mixture of Gaussians for the two clusters. This process is aborted when the current bin is assigned to a different cluster than its predecessor. The method does not envolve an exhaustive search. Visual examples of our segmentation versus Otsu's thresholding method are presented. © 2013 IEEE.

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Keywords
Gaussian kernel, Kde, Lmage processing, Thresholding, Gaussian kernels, Image histograms, Kde, Mixture of Gaussians, Thresholding, Thresholding methods, Gaussian distribution, Iterative methods, Mixtures, Signal processing, Graphic methods
Citation
Published Version (Please cite this version)