de.lmu.ifi.dbs.jfeaturelib.shapeFeatures

Class CentroidBoundaryDistance

java.lang.Object

de.lmu.ifi.dbs.jfeaturelib.features.AbstractFeatureDescriptor

de.lmu.ifi.dbs.jfeaturelib.shapeFeatures.CentroidBoundaryDistance

All Implemented Interfaces:

Descriptor, FeatureDescriptor

public class CentroidBoundaryDistance
extends AbstractFeatureDescriptor

Computes a normalized distance shape feature as Array List containing the max distances measured for each angle or null if no boundary was found at that angle. This algorithm is described in "Yang Mingqiang, Kpalma Kidiyo and Ronsin Joseph (2008). A Survey of Shape Feature Extraction Techniques, Pattern Recognition Techniques, Technology and Applications, Peng-Yeng Yin (Ed.), ISBN: 978-953-7619-24-4, InTech, Available from: http://www.intechopen.com/articles/show/title/a_survey_of_shape_feature_extraction_techniques " as "centroid-to-boundary distance approach".

Since:

09/29/2012

Author:

Johannes Stadler

Nested Class Summary

Nested classes/interfaces inherited from interface de.lmu.ifi.dbs.jfeaturelib.Descriptor

Descriptor.Supports

Field Summary

Fields inherited from class de.lmu.ifi.dbs.jfeaturelib.features.AbstractFeatureDescriptor

pcs

Fields inherited from interface de.lmu.ifi.dbs.jfeaturelib.Descriptor

DOES_ALL

Constructor Summary

Constructors

Constructor and Description
CentroidBoundaryDistance() Constructs a CentroidBoundaryDistance object with distances measured all 22,5°
CentroidBoundaryDistance(int angles) Constructs a CentroidBoundaryDistance object

Method Summary

Methods

Modifier and Type	Method and Description
double	distance(int x1, int y1, int x2, int y2)
void	generateFeatures()
String	getDescription() Returns a short plain Text description about the Descriptor and the semantics of the double array obtained from FeatureDescriptor.getFeatures().
ArrayList	getDistances()
void	run(ij.process.ImageProcessor ip) Start processing of this algorithm on the given image processor.
EnumSet<Descriptor.Supports>	supports() Determine the capabilities of this algorithm.
ij.process.ImageProcessor	thicken(ij.process.ImageProcessor ip)

Methods inherited from class de.lmu.ifi.dbs.jfeaturelib.features.AbstractFeatureDescriptor

addData, addData, addData, addPropertyChangeListener, endProgress, firePropertyChange, getFeatures, getMask, inMask, setMask, setProperties, startProgress

Methods inherited from class java.lang.Object

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

Constructor Detail

CentroidBoundaryDistance

public CentroidBoundaryDistance()

Constructs a CentroidBoundaryDistance object with distances measured all 22,5°

CentroidBoundaryDistance

public CentroidBoundaryDistance(int angles)

Constructs a CentroidBoundaryDistance object

Parameters:

angles - Number of angles, i.e. 36 for measurements all 10°

Method Detail

getDistances

public ArrayList getDistances()

distance

public double distance(int x1,
              int y1,
              int x2,
              int y2)

thicken

public ij.process.ImageProcessor thicken(ij.process.ImageProcessor ip)

run

public void run(ij.process.ImageProcessor ip)

Description copied from interface: Descriptor

Start processing of this algorithm on the given image processor. Keep in mind that if the imageProcessor is changed, Supports.NoChanges must not be set. This is also the case even if only ImageProcessor.snapshot() is used.

generateFeatures

public void generateFeatures()

supports

public EnumSet<Descriptor.Supports> supports()

Description copied from interface: Descriptor

Determine the capabilities of this algorithm.

Specified by:

supports in interface Descriptor

Overrides:

supports in class AbstractFeatureDescriptor

Returns:

the set of supported capabilities.

getDescription

public String getDescription()

Description copied from interface: FeatureDescriptor

Returns a short plain Text description about the Descriptor and the semantics of the double array obtained from FeatureDescriptor.getFeatures(). May return null if no description is implemented - even though this should be avoided by any means.

Returns:

semantic description of getFeatures or null.