boofcv.alg.feature.orientation

Class OrientationAverage<D extends boofcv.struct.image.ImageGray>

java.lang.Object

boofcv.alg.feature.orientation.OrientationAverage<D>

All Implemented Interfaces:

OrientationGradient<D>, RegionOrientation

Direct Known Subclasses:

ImplOrientationAverage_F32, ImplOrientationAverage_S16, ImplOrientationAverage_S32

public abstract class OrientationAverage<D extends boofcv.struct.image.ImageGray>
extends java.lang.Object
implements OrientationGradient<D>

Computes the orientation of a region by summing up the derivative along each axis independently then computing the direction fom the sum. If weighted a Gaussian kernel centered around the targeted pixel is used.

Field Summary

Fields

Modifier and Type	Field and Description
protected D	derivX
protected D	derivY
protected boolean	isWeighted
protected double	objectToSample
protected int	radiusScale
protected boofcv.struct.ImageRectangle	rect
protected int	sampleRadius
protected boofcv.struct.convolve.Kernel2D_F32	weights

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	OrientationAverage(double objectRadiusToScale, boolean weighted)

Method Summary

Modifier and Type	Method and Description
double	compute(double X, double Y) Computes the orientation of a region about its center.
protected abstract double	computeUnweightedScore() Compute the score without using the optional weights
protected abstract double	computeWeightedScore(int c_x, int c_y) Compute the score using the weighting kernel.
int	getSampleRadius()
boofcv.struct.convolve.Kernel2D_F32	getWeights()
void	setImage(D derivX, D derivY) Specifies input image data for estimating orientation.
void	setObjectRadius(double radius) Specifies the circle's radius that the orientation should be
void	setSampleRadius(int sampleRadius)

Methods inherited from class java.lang.Object

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

Methods inherited from interface boofcv.abst.feature.orientation.OrientationGradient

getImageType

Field Detail

derivX

protected D extends boofcv.struct.image.ImageGray derivX

derivY

protected D extends boofcv.struct.image.ImageGray derivY

rect

protected boofcv.struct.ImageRectangle rect

objectToSample

protected double objectToSample

sampleRadius

protected int sampleRadius

radiusScale

protected int radiusScale

isWeighted

protected boolean isWeighted

weights

protected boofcv.struct.convolve.Kernel2D_F32 weights

Constructor Detail

OrientationAverage

protected OrientationAverage(double objectRadiusToScale,
                             boolean weighted)

Method Detail

getSampleRadius

public int getSampleRadius()

setSampleRadius

public void setSampleRadius(int sampleRadius)

getWeights

public boofcv.struct.convolve.Kernel2D_F32 getWeights()

setObjectRadius

public void setObjectRadius(double radius)

Description copied from interface: RegionOrientation

Specifies the circle's radius that the orientation should be

Specified by:

setObjectRadius in interface RegionOrientation

Parameters:

radius - Object's radius.

setImage

public void setImage(D derivX,
                     D derivY)

Description copied from interface: OrientationGradient

Specifies input image data for estimating orientation.

Specified by:

setImage in interface OrientationGradient<D extends boofcv.struct.image.ImageGray>

Parameters:

derivX - Image derivative along x-axis.

derivY - Image derivative along y-axis.

compute

public double compute(double X,
                      double Y)

Description copied from interface: RegionOrientation

Computes the orientation of a region about its center.

Specified by:

compute in interface RegionOrientation

Parameters:

X - Center of the region in image pixels.

Y - Center of the region in image pixels.

Returns:

Orientation in radians. Angle zero points along x-axis and pi/2 along y-axis.

computeUnweightedScore

protected abstract double computeUnweightedScore()

Compute the score without using the optional weights

computeWeightedScore

protected abstract double computeWeightedScore(int c_x,
                                               int c_y)

Compute the score using the weighting kernel.