• Title/Summary/Keyword: Muitidimensional Gaussian PDF

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IMAGE SEGMENTATION BASED ON THE STATISTICAL VARIATIONAL FORMULATION USING THE LOCAL REGION INFORMATION

  • Park, Sung Ha;Lee, Chang-Ock;Hahn, Jooyoung
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.2
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    • pp.129-142
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    • 2014
  • We propose a variational segmentation model based on statistical information of intensities in an image. The model consists of both a local region-based energy and a global region-based energy in order to handle misclassification which happens in a typical statistical variational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small difference between two Gaussian distributions. Based on statistical information restricted to the local ambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of the proposed variational model.