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ACCV
2007
Springer

Image Segmentation Using Iterated Graph Cuts Based on Multi-scale Smoothing

10 years 9 months ago
Image Segmentation Using Iterated Graph Cuts Based on Multi-scale Smoothing
We present a novel approach to image segmentation using iterated Graph Cuts based on multi-scale smoothing. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the previous process, and set the probability as the t-link of the graph for the next process. The proposed method can segment the regions of an object with a stepwise process from global to local segmentation by iterating the graph-cuts process with Gaussian smoothing using different values for the standard deviation. We demonstrate that we can obtain 4.7% better segmentation than that with the conventional approach.
Tomoyuki Nagahashi, Hironobu Fujiyoshi, Takeo Kana
Added 06 Jun 2010
Updated 06 Jun 2010
Type Conference
Year 2007
Where ACCV
Authors Tomoyuki Nagahashi, Hironobu Fujiyoshi, Takeo Kanade
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