Abstract
The Hausdorff Voronoi diagram of clusters of points in the plane is a generalization of Voronoi diagrams based on the Hausdorff distance function. Its combinatorial complexity is \(O(n+m)\), where n is the total number of points and \(m\) is the number of crossings between the input clusters (\(m=O(n^2)\)); the number of clusters is k. We present efficient algorithms to construct this diagram following the randomized incremental construction (RIC) framework (Clarkson and Shor in Discrete Comput Geom 4:387–421, 1989; Clarkson et al. in Comput Geom Theory Appl 3(4):185–212, 1993). Our algorithm for non-crossing clusters (\(m=0\)) runs in expected \(O(n\log {n} + k\log n \log k)\) time and deterministic O(n) space. The algorithm for arbitrary clusters runs in expected \(O((m+n\log {k})\log {n})\) time and \(O(m+n\log {k})\) space. The two algorithms can be combined in a crossing-oblivious scheme within the same bounds. We show how to apply the RIC framework to handle non-standard characteristics of generalized Voronoi diagrams, including sites (and bisectors) of non-constant complexity, sites that are not enclosed in their Voronoi regions, empty Voronoi regions, and finally, disconnected bisectors and disconnected Voronoi regions. The Hausdorff Voronoi diagram finds direct applications in VLSI CAD.
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Notes
Other metrics, such as the \(L_p\) metric, are possible.
The time complexity claimed in Dehne et al. is \(O(n\log ^4{n})\), however, in reality the described algorithm requires \(O(n\log ^5{n})\) time (Maheshwari 2018).
To avoid confusion with Voronoi regions we use the term ranges in this paper.
Note that some of the new ranges of type (2) in fact consist of portions of two or more distinct old ranges. However, here we treat each such range as a group of ranges, as subdivided by old ranges. After the vertex lists of this group are found, it is easy to merge these ranges into a single range, and their vertex lists into a single list.
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Research supported in part by the Swiss National Science Foundation, projects SNF 20GG21-134355 (ESF EUROCORES EuroGIGA/VORONOI) and SNF 200021E-154387. E. A. was also supported partially by F.R.S.-FNRS and SNF grant P2TIP2-168563 under the SNF Early PostDoc Mobility program.
E. Arseneva: Research performed mainly while at the Università della Svizzera italiana (USI).
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Arseneva, E., Papadopoulou, E. Randomized incremental construction for the Hausdorff Voronoi diagram revisited and extended. J Comb Optim 37, 579–600 (2019). https://doi.org/10.1007/s10878-018-0347-x
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DOI: https://doi.org/10.1007/s10878-018-0347-x