boofcv.alg.fiducial.calib.squares

Class SquaresIntoRegularClusters

java.lang.Object

boofcv.alg.fiducial.calib.squares.SquaresIntoClusters

boofcv.alg.fiducial.calib.squares.SquaresIntoRegularClusters

public class SquaresIntoRegularClusters
extends SquaresIntoClusters

Processes the detected squares in the image and connects them into clusters. Squares can be connected to each other if two equivalent sides are parallel and their distance apart is "reasonable". The parallel requirement take advantage of line under perspective distortion remaining parallel.

Field Summary

Fields

Modifier and Type	Field and Description
int	maxNeighbors

Constructor Summary

Constructors

Constructor and Description
SquaresIntoRegularClusters(double spaceToSquareRatio, int maxNeighbors, double maxNeighborDistanceRatio) Declares data structures and configures algorithm

Method Summary

Modifier and Type	Method and Description
java.util.List<java.util.List<SquareNode>>	process(java.util.List<Polygon2D_F64> squares) Processes the unordered set of squares and creates a graph out of them using prior knowledge and geometric constraints.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

maxNeighbors

public int maxNeighbors

Constructor Detail

SquaresIntoRegularClusters

public SquaresIntoRegularClusters(double spaceToSquareRatio,
                                  int maxNeighbors,
                                  double maxNeighborDistanceRatio)

Declares data structures and configures algorithm

Parameters:

spaceToSquareRatio - Ratio of space between squares to square lengths

maxNeighbors - The maximum number of neighbors it will look at when connecting a node

maxNeighborDistanceRatio - Maximum distance away a neighbor can be from a square to be connected. Relative to the size of the square. Try 1.35

Method Detail

process

public java.util.List<java.util.List<SquareNode>> process(java.util.List<Polygon2D_F64> squares)

Processes the unordered set of squares and creates a graph out of them using prior knowledge and geometric constraints.

Parameters:

squares - Set of squares

Returns:

List of graphs. All data structures are recycled on the next call to process().