![voronoi diagrams voronoi diagrams](https://i.ytimg.com/vi/41LFIoW4VHQ/maxresdefault.jpg)
A Voronoi diagram will contain n regions. Each region contains the set of points that are closest to a particular seed. The starting point for calculating a Voronoi diagram is a set of n seeds, points that are located in the two dimensional space.
![voronoi diagrams voronoi diagrams](https://rosettagit.org/tasks/voronoi-diagram/c.png)
Voronoi diagrams divide a two dimensional space into regions. The process is repeated recursively until the entire diagram has been calculated appropriately. If the corners belong to the same region, there is no need to subdivide this quadrant anymore but if they are different than the original quadrant is subdivided into smaller quadrants. Rather than calculate every position, our approach calculates the positions at the four corners of a quadrant. This paper introduces a new algorithm to compute discretized Voronoi Diagrams using a divide-and-conquer approach. Naive approaches to generating discretized Voronoi Diagrams require every discretized position to be analyzed with the set of locations. Problematically, the initial computations required to generate a Voronoi Diagram can be computationally expensive. However, Voronoi Diagrams precompute the geometric areas that each of these locations is closest to in order to ameliorate the cost of computing distances later on. Identifying the closest of a set of locations typically requires computing the distance to each of these locations, given a current position.