Delaunay triangulation

In mathematics, and computational geometry, the Delaunay triangulation or Delone triangularization for a set P of points in the plane is the triangulation DT(P) of P such that no point in P is inside the circumcircle of any triangle in DT(P). Delaunay triangulations maximize the minimum angle of all the angles of the triangles in the triangulation; they tend to avoid "sliver" triangles. The triangulation was invented by Boris Delaunay in 1934 .

Related Topics:
Mathematics - Computational geometry - Triangulation - Circumcircle - Triangle - Boris Delaunay - [1]

~ ~ ~ ~ ~ ~ ~ ~ ~ ~

In the general n-dimensional case it is stated as follows: For a set P of points in the (n-dimensional) Euclidean space, the Delaunay triangulation is the triangulation DT(P) of P such that no point in P is inside the circum-hypersphere of any simplex in DT(P).

Related Topics:
Euclidean space - Triangulation - Circum-hypersphere - Simplex

~ ~ ~ ~ ~ ~ ~ ~ ~ ~

Equivalently, the Delaunay triangulation of a discrete point set P is the geometric dual of the Voronoi tessellation for P.

Related Topics:
Triangulation - Discrete - Geometric dual - Voronoi tessellation

~ ~ ~ ~ ~ ~ ~ ~ ~ ~

It is known that the Delaunay triangulation exists and is unique for P, if P is a set of points in general position; that is, no three points are on the same line and no four are on the same circle, for a two dimensional set of points, or no n + 1 points are on the same hyperplane and no n + 2 points are on the same hypersphere, for an n-dimensional set of points. An elegant proof of this fact is outlined below. It is worth mentioning, because it reveals connections between the two constructs fundamental for computational and combinatorial geometry.

Related Topics:
General position - Computational - Combinatorial geometry

~ ~ ~ ~ ~ ~ ~ ~ ~ ~

The problem of finding the Delaunay triangulation of a set of points in n-dimensional Euclidean space can be converted to the problem of finding the convex hull of a set of points in (n + 1)-dimensional space, by giving each point p an extra coordinate equal to |p|^2, taking the bottom side of the convex hull, and mapping back to n-dimensional space by deleting the last coordinate. As the convex hull is unique, so is the triangulation, assuming all facets of the convex hull are simplexes. A facet not being a simplex implies that n + 2 of the original points lay on the same d-hypersphere, and the points were not in general position.

Related Topics:
Convex hull - Simplex - Hypersphere

~ ~ ~ ~ ~ ~ ~ ~ ~ ~

On the other hand, it is easily seen that for the set of three points on the same line there is no Delaunay triangulation (in fact, no triangulation at all). On the other hand, for 4 points on the same circle (e.g., the vertices of a rectangle) the Delaunay triangulation is not unique: clearly, the two possible triangulations that split the quadrangle into two triangles satisfy the Delaunay condition.

~ ~ ~ ~ ~ ~ ~ ~ ~ ~

Generalizations are possible to metrics other than Euclidean. However in these cases the Delaunay triangulation is not guaranteed to exist or be unique.

~ ~ ~ ~ ~ ~ ~ ~ ~ ~