boofcv.alg.fiducial.calib.circle

Class EllipsesIntoClusters

java.lang.Object

boofcv.alg.fiducial.calib.circle.EllipsesIntoClusters

public class EllipsesIntoClusters
extends java.lang.Object

Given an unordered list of ellipses found in the image connect them into clusters. A cluster of ellipses will be composed of ellipses which are spatially close to each other and have major axises which are of similar size.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	EllipsesIntoClusters.Node

Constructor Summary

Constructors

Constructor and Description
EllipsesIntoClusters(double maxDistanceToMajorAxisRatio, double sizeSimilarityTolerance, double edgeIntensitySimilarityTolerance) Configures clustering

Method Summary

Modifier and Type	Method and Description
double	getMaxDistanceToMajorAxisRatio()
int	getMinimumClusterSize()
double	getSizeSimilarityTolerance()
void	process(java.util.List<boofcv.alg.shapes.ellipse.BinaryEllipseDetector.EllipseInfo> ellipses, java.util.List<java.util.List<EllipsesIntoClusters.Node>> output) Processes the ellipses and creates clusters.
void	setMaxDistanceToMajorAxisRatio(double maxDistanceToMajorAxisRatio)
void	setMinimumClusterSize(int minimumClusterSize)
void	setSizeSimilarityTolerance(double sizeSimilarityTolerance)

Methods inherited from class java.lang.Object

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

Constructor Detail

EllipsesIntoClusters

public EllipsesIntoClusters(double maxDistanceToMajorAxisRatio,
                            double sizeSimilarityTolerance,
                            double edgeIntensitySimilarityTolerance)

Configures clustering

Parameters:

maxDistanceToMajorAxisRatio - The maximum distance away the center of another ellipse that will be considered specifies as a multiple of the ellipse's major axis

sizeSimilarityTolerance - How similar two ellipses must be to be connected. 0 to 1.0. 1.0 = perfect match and 0.0 = infinite difference in size

edgeIntensitySimilarityTolerance - How similar the intensity of the ellipses edges need to be. 0 to 1.0. 1.0 = perfect

Method Detail

process

public void process(java.util.List<boofcv.alg.shapes.ellipse.BinaryEllipseDetector.EllipseInfo> ellipses,
                    java.util.List<java.util.List<EllipsesIntoClusters.Node>> output)

Processes the ellipses and creates clusters.

Parameters:

ellipses - Set of unordered ellipses

output - Resulting found clusters. Cleared automatically. Returned lists are recycled on next call.

getMaxDistanceToMajorAxisRatio

public double getMaxDistanceToMajorAxisRatio()

setMaxDistanceToMajorAxisRatio

public void setMaxDistanceToMajorAxisRatio(double maxDistanceToMajorAxisRatio)

getSizeSimilarityTolerance

public double getSizeSimilarityTolerance()

setSizeSimilarityTolerance

public void setSizeSimilarityTolerance(double sizeSimilarityTolerance)

getMinimumClusterSize

public int getMinimumClusterSize()

setMinimumClusterSize

public void setMinimumClusterSize(int minimumClusterSize)