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- W2249132072 abstract "The Chan-Vese model is a successful Variational segmentation model for piecewise constant and smooth images. However, it is failed to detect tigers or leopards in an image. In this paper, we propose a modified model that segments tiger into a whole object. Our energy functional uses an improved fitting term based on local histogram and the energy minimizing is therefore looking for homogeneous histograms to distinguish objects. We present a numerical algorithm to compute the corresponding partial differential equation. The proposed model yields excellent performance on synthetic images and images from the Berkeley segmentation data set 500." @default.
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- W2249132072 date "2015-08-01" @default.
- W2249132072 modified "2023-09-25" @default.
- W2249132072 title "A local histogram based Chan-Vese model for segmentation" @default.
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- W2249132072 doi "https://doi.org/10.1109/icnc.2015.7378058" @default.
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