Voronoi diagram belong to classical problems of the computational geometry. Its origin dates
back into 1850 when it was considered by Dirichlet. The rigid mathematical fundamental was
given by Voronoi in 1908.
Let us have points p_{i}, 0 < i <= n in ndimensional space P.
The set of all points with property that every point inside the cell is closer to point
p_{i} than to any other point from P represents the Voronoi cell
(Figure 1). The union of all Voronoi cells is known as Voronoi diagram.
Figure 1: Voronoi cell
As seen from Figure 1, the construction of Voronoi diagram consists of repetitive subdivisions
of the space determined by the input points into subspaces to meet the Voronoi criteria:
In many aplications, Voronoi diagrams are already the final solution. For example, study of
behavior and maintainance of live creature, which are depended on number of neighbors with whom
they are fighting for food and lightness is exactly what Voronoi diagram expresses. However,
having a Voronoi diagram, many important geometric features like searching for the closest neighbor,
Delaunay triangulation, searching for the largest empty circle, minimum spanning tree (Euclidean
tree), can be determined in the linear time.
The first reiable algorithm for construction has been published by
Green and Sibson [GREE77], although the Voronoi diagrams have been known
for a long time. This approach used incremental method and worked in
O(n^{2}) time. The first algorithm
requiring O(n log_{2} n) was suggested by Shamos and Hoey (1975)
[PREP85] using divide and conquer approach. However, its implementation is complicated. In
1985, Fortune presented more elegant approach and it is described in [BERG97, O'ROU93]. In this
paper, we consider primarily the data structures needed for the construction. In 1986,
Edelsbruner and Seidel discovered beautiful connection between Voronoi diagram and convex
hulls in one higher dimension [O'ROU93]. This method has some beautiful properties and it is
becoming more and more popular.
