Image histogram thresholding using Gaussian kernel density estimation (English)
2013 21st Signal Processing and Communications Applications Conference (SIU)
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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.
Mixture of Gaussians
Published Version (Please cite this version)http://dx.doi.org/10.1109/SIU.2013.6531341
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