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      Image histogram thresholding using Gaussian kernel density estimation (English)

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      Author
      Suhre, Alexander
      Çetin, A. Enis
      Date
      2013
      Source Title
      2013 21st Signal Processing and Communications Applications Conference (SIU)
      Publisher
      IEEE
      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.
      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
      Permalink
      http://hdl.handle.net/11693/27992
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2013.6531341
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      • Department of Electrical and Electronics Engineering 3524
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