Faster Fuzzy Connectedness via Precomputation
We propose a method for accelerating the computation of fuzzy connectedness. The method is based on a precomputation step – the construction of a supervertex graph whose vertices are clusters of image elements. By constructing this supervertex graph in a specific way, we can perform the bulk of the fuzzy connectedness computations on this graph, rather than on the original image, while guaranteeing exact results. Typically, the number of nodes in the supervertex graph is much smaller than the number of elements in the image, and thus less computation is required. In an experiment, we demonstrate the ability of the proposed method to accelerate the computation of fuzzy connectedness considerably.
KeywordsFuzzy Connectedness Supervertex graph Interactive segmentation
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- 3.Falcão, A.X., Bergo, F.P.G.: Interactive volume segmentation with differential image foresting transforms. IEEE MI 23(9), 1100–1108 (2004)Google Scholar
- 7.Zhuge, Y., Cao, Y., Miller, R.W.: GPU accelerated fuzzy connected image segmentation by using CUDA. In: Engineering in Medicine and Biology Society, EMBC 2009. Annual International Conference of the IEEE, pp. 6341–6344 (2009)Google Scholar