GEOS
3.9.0dev

An algorithm for computing a distance metric which is an approximation to the Hausdorff Distance based on a discretization of the input geom::Geometry. More...
#include <DiscreteHausdorffDistance.h>
Public Member Functions  
DiscreteHausdorffDistance (const geom::Geometry &p_g0, const geom::Geometry &p_g1)  
void  setDensifyFraction (double dFrac) 
double  distance () 
double  orientedDistance () 
const std::array < geom::Coordinate, 2 >  getCoordinates () const 
Static Public Member Functions  
static double  distance (const geom::Geometry &g0, const geom::Geometry &g1) 
static double  distance (const geom::Geometry &g0, const geom::Geometry &g1, double densifyFrac) 
An algorithm for computing a distance metric which is an approximation to the Hausdorff Distance based on a discretization of the input geom::Geometry.
The algorithm computes the Hausdorff distance restricted to discrete points for one of the geometries. The points can be either the vertices of the geometries (the default), or the geometries with line segments densified by a given fraction. Also determines two points of the Geometries which are separated by the computed distance.
This algorithm is an approximation to the standard Hausdorff distance. Specifically,
for all geometries a, b: DHD(a, b) <= HD(a, b)
The approximation can be made as close as needed by densifying the input geometries. In the limit, this value will approach the true Hausdorff distance:
DHD(A, B, densifyFactor) > HD(A, B) as densifyFactor > 0.0
The default approximation is exact or close enough for a large subset of useful cases. Examples of these are:
An example where the default approximation is not close is:
A = LINESTRING (0 0, 100 0, 10 100, 10 100) B = LINESTRING (0 100, 0 10, 80 10)
DHD(A, B) = 22.360679774997898 HD(A, B) ~= 47.8

inline 
Sets the fraction by which to densify each segment. Each segment will be (virtually) split into a number of equallength subsegments, whose fraction of the total length is closest to the given fraction.
dFrac 