de.lmu.ifi.dbs.jfeaturelib.features

Class CEDD

java.lang.Object

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

de.lmu.ifi.dbs.jfeaturelib.features.CEDD

All Implemented Interfaces:

Descriptor, FeatureDescriptor

public class CEDD
extends AbstractFeatureDescriptor

The CEDD feature was created, implemented and provided by Savvas A. Chatzichristofis More information can be found in: Savvas A. Chatzichristofis and Yiannis S. Boutalis, CEDD: Color and Edge Directivity Descriptor. A Compact Descriptor for Image Indexing and Retrieval, A. Gasteratos, M. Vincze, and J.K. Tsotsos (Eds.): ICVS 2008, LNCS 5008, pp. 312-322, 2008. This is a wrapper class for the corresponding lire class

See Also:

CEDD

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
CEDD() Constructor with default parameters
CEDD(double Th0, double Th1, double Th2, double Th3, boolean compactDescriptor) Constructs new CEDD descriptor

Method Summary

Methods

Modifier and Type	Method and Description
net.semanticmetadata.lire.imageanalysis.CEDD	getCedd() Returns the cedd instance from LIRE.
boolean	getCompact() Compact output of results
String	getDescription() Returns a short plain Text description about the Descriptor and the semantics of the double array obtained from FeatureDescriptor.getFeatures().
double	getT0() Treshold for edge detection
double	getT1() Treshold for non-directional edges
double	getT2() Treshold for horizontal and vertical edges
double	getT3() Treshold for diagonal edges
void	run(ij.process.ImageProcessor ip) Start processing of this algorithm on the given image processor.
void	setCedd(net.semanticmetadata.lire.imageanalysis.CEDD cedd)
void	setCompact(boolean compact) Compact output of results
void	setProperties(LibProperties properties) Injects the properties class that can be used to retrieve several properties.
void	setT0(double t0) Treshold for edge detection
void	setT1(double t1) Treshold for non-directional edges
void	setT2(double t2) Treshold for horizontal and vertical edges
void	setT3(double t3) Treshold for diagonal edges
EnumSet<Descriptor.Supports>	supports() Determine the capabilities of this algorithm.

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

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

Methods inherited from class java.lang.Object

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

Constructor Detail

CEDD

public CEDD()

Constructor with default parameters

CEDD

public CEDD(double Th0,
    double Th1,
    double Th2,
    double Th3,
    boolean compactDescriptor)

Constructs new CEDD descriptor

Parameters:

Th0 - Treshold for edge detection

Th1 - Treshold for non-directional edges

Th2 - Treshold for horizontal and vertical edges

Th3 - Treshold for diagonal edges

compactDescriptor - Compact output of results

Method Detail

setProperties

public void setProperties(LibProperties properties)
                   throws IOException

Description copied from interface: FeatureDescriptor

Injects the properties class that can be used to retrieve several properties.

Specified by:

setProperties in interface FeatureDescriptor

Overrides:

setProperties in class AbstractFeatureDescriptor

Throws:

IOException - if something went wrong

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.

getCedd

public net.semanticmetadata.lire.imageanalysis.CEDD getCedd()

Returns the cedd instance from LIRE. The instance is available only after the run method has been called.

Returns:

the LIRE CEDD instance

setCedd

public void setCedd(net.semanticmetadata.lire.imageanalysis.CEDD cedd)

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.

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.

getT0

public double getT0()

Treshold for edge detection

Returns:

Treshold for edge detection

setT0

public void setT0(double t0)

Treshold for edge detection

Parameters:

t0 - Treshold for edge detection

getT1

public double getT1()

Treshold for non-directional edges

Returns:

Treshold for non-directional edges

setT1

public void setT1(double t1)

Treshold for non-directional edges

Parameters:

t1 - Treshold for non-directional edges

getT2

public double getT2()

Treshold for horizontal and vertical edges

Returns:

Treshold for horizontal and vertical edges

setT2

public void setT2(double t2)

Treshold for horizontal and vertical edges

Parameters:

t2 - Treshold for horizontal and vertical edges

getT3

public double getT3()

Treshold for diagonal edges

Returns:

Treshold for diagonal edges

setT3

public void setT3(double t3)

Treshold for diagonal edges

Parameters:

t3 - Treshold for diagonal edges

getCompact

public boolean getCompact()

Compact output of results

Returns:

Compact output of results

setCompact

public void setCompact(boolean compact)

Compact output of results

Parameters:

compact - Compact output of results