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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References
Ciesielski, K.C., Udupa, J.K.: Affinity functions in fuzzy connectedness based image segmentation i: Equivalence of affinities. Computer Vision and Image Understanding 114(1), 146–154 (2010)
Ciesielski, K.C., Udupa, J.K.: Affinity functions in fuzzy connectedness based image segmentation ii: Defining and recognizing truly novel affinities. Computer Vision and Image Understanding 114(1), 155–166 (2010)
Falcão, A.X., Bergo, F.P.G.: Interactive volume segmentation with differential image foresting transforms. IEEE MI 23(9), 1100–1108 (2004)
Nyúl, L.G., Falcão, A.X., Udupa, J.K.: Fuzzy-connected 3D image segmentation at interactive speeds. Graph. Models 64(5), 259–281 (2002)
Soille, P., Najman, L.: On morphological hierarchical representations for image processing and spatial data clustering. In: Köthe, U., Montanvert, A., Soille, P. (eds.) WADGMM 2010. LNCS, vol. 7346, pp. 43–67. Springer, Heidelberg (2012)
Udupa, J.K., Samarasekera, S.: Fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation. Graphical Models and Image Processing 58(3), 246–261 (1996)
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)
Zhuge, Y., Udupa, J.K., Saha, P.K.: Vectorial scale-based fuzzy-connected image segmentation. Computer Vision and Image Understanding 101(3), 177–193 (2006)
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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
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