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Weighted fusion graphs: Merging properties and watersheds

机译:加权融合图:合并属性和分水岭

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This paper deals with the mathematical properties of watersheds in weighted graphs linked to region merging methods, as used in image analysis. In a graph, a cleft (or a binary watershed) is a set of vertices that cannot be reduced, by point removal, without changing the number of regions (connected components) of its complement. To obtain a watershed adapted to morphological region merging, it has been shown that one has to use the topological thinnings introduced by M. Couprie and G. Bertrand. Unfortunately, topological thinnings do not always produce thin clefts. Therefore, we introduce a new transformation on vertex weighted graphs, called C-watershed, that always produces a cleft. We present the class of perfect fusion graphs, for which any two neighboring regions can be merged, while preserving all other regions, by removing from the cleft the points adjacent to both. An important theorem of this paper states that, on these graphs, the C-watersheds are topological thinnings and the corresponding divides are thin clefts. We propose a linear-time immersion-like algorithm to compute C-watersheds on perfect fusion graphs, whereas, in general, a linear-time topological thinning algorithm does not exist. Furthermore, we prove that this algorithm is monotone in the sense that the vertices are processed in increasing order of weight. Finally, we derive some characterizations of perfect fusion graphs based on the thinness properties of both C-watersheds and topological watersheds. (C) 2008 Elsevier B.V. All rights reserved.
机译:本文在图像分析中使用与区域合并方法相关联的加权图中的分水岭的数学性质。在图形中,裂缝(或二元分水岭)是一组顶点,这些顶点不能通过点移除而被缩小,而无需更改其补集的区域(连接的组件)的数量。为了获得适合于形态学区域合并的分水岭,已表明必须使用M. Couprie和G. Bertrand引入的拓扑稀化。不幸的是,拓扑变薄并不总是产生薄裂痕。因此,我们在顶点加权图上引入了一个新的变换,称为C分水岭,它总是产生裂隙。我们提出了完美的融合图类,可以通过从裂缝中去除与两个区域相邻的点来合并任意两个相邻区域,同时保留所有其他区域。本文的一个重要定理指出,在这些图中,C分水岭是拓扑变薄,而相应的分度是薄裂口。我们提出了一种类似于线性时间浸入的算法来计算完美融合图上的C分水岭,而通常情况下,线性时间拓扑稀疏算法并不存在。此外,我们证明了该算法是单调的,因为顶点按权重的递增顺序进行处理。最后,我们基于C分水岭和拓扑分水岭的薄度特性,得出了完美融合图的一些特征。 (C)2008 Elsevier B.V.保留所有权利。

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