Abstract
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.
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Malmberg, F., Strand, R. (2013). Faster Fuzzy Connectedness via Precomputation. In: Hendriks, C.L.L., Borgefors, G., Strand, R. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2013. Lecture Notes in Computer Science, vol 7883. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38294-9_40
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DOI: https://doi.org/10.1007/978-3-642-38294-9_40
Publisher Name: Springer, Berlin, Heidelberg
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