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• W1983680719 abstract "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." @default.
• W1983680719 created "2016-06-24" @default.
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• W1983680719 date "2014-06-25" @default.
• W1983680719 modified "2023-09-24" @default.
• W1983680719 title "IMAGE SEGMENTATION BASED ON THE STATISTICAL VARIATIONAL FORMULATION USING THE LOCAL REGION INFORMATION" @default.
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• W1983680719 doi "https://doi.org/10.12941/jksiam.2014.18.129" @default.
• W1983680719 hasPublicationYear "2014" @default.
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