Package boofcv.alg.feature.detect.selector

Class FeatureSelectUniformBest<Point>

java.lang.Object

boofcv.alg.feature.detect.selector.FeatureSelectUniformBest<Point>

All Implemented Interfaces:

FeatureSelectLimitIntensity<Point>

public class FeatureSelectUniformBest<Point>
extends Object
implements FeatureSelectLimitIntensity<Point>

Attempts to select features uniformly across the image with a preference for locally more intense features. This is done by breaking the image up into a grid. Then features are added by selecting the most intense feature from each grid. If a cell has a prior feature in it then it is skipped for that iteration and the prior counter is decremented. This is repeated until the limit has been reached or there are no more features to add.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	FeatureSelectUniformBest.Info<Point>	Info for each cell

Field Summary

Fields

Modifier and Type	Field	Description
ConfigGridUniform	configUniform	Configuration for uniformly selecting a grid

Constructor Summary

Constructors

Constructor	Description
FeatureSelectUniformBest()
FeatureSelectUniformBest(SampleIntensity<Point> sampler)

Method Summary

Modifier and Type	Method	Description
protected FeatureSelectUniformBest.Info<Point>	getGridCell(Point p)	Returns the grid cell that contains the point
void	select(@Nullable GrayF32 intensity, int width, int height, boolean positive, @Nullable FastAccess<Point> prior, FastAccess<Point> detected, int limit, FastArray<Point> selected)	Selects features using a rule given the limit on detection objects.
void	setSampler(SampleIntensity<Point> sampler)	Specifies how the intensity will be sampled.

Methods inherited from class java.lang.Object

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

Field Details

configUniform

public ConfigGridUniform configUniform

Configuration for uniformly selecting a grid

Constructor Details

FeatureSelectUniformBest

public FeatureSelectUniformBest(SampleIntensity<Point> sampler)

FeatureSelectUniformBest

public FeatureSelectUniformBest()

Method Details

select

public void select(@Nullable
 @Nullable GrayF32 intensity,
 int width,
 int height,
 boolean positive,
 @Nullable
 @Nullable FastAccess<Point> prior,
 FastAccess<Point> detected,
 int limit,
 FastArray<Point> selected)

Description copied from interface: FeatureSelectLimitIntensity

Selects features using a rule given the limit on detection objects. If the limit is higher than the number of detected features and prior is null then the detected features should be copied into selected. How prior features are used is dependent upon the implementation and their affect isn't specified in general.

NOTE: The reason a null input image is supported is for the situation where the intensity image is no longer available and intensity has been copied into points. See SIFT

Specified by:

select in interface FeatureSelectLimitIntensity<Point>

Parameters:

intensity - (Input) Intensity image. If null that means the point will provide intensity information. Nullable.

width - (Input) if image is null then this must be the image's width

height - (Input) if image is null then this must be the image's height

positive - (Input) true if better features have more positive values, false if it's more negative values

prior - (Input) Locations of previously detected features. Nullable

detected - (Input) Locations of newly detected features

limit - (Input) The maximum number of new features detected

selected - (Output) Selected features. Element count not exceed the limit. Reset on every call.

setSampler

public void setSampler(SampleIntensity<Point> sampler)

Description copied from interface: FeatureSelectLimitIntensity

Specifies how the intensity will be sampled.

Specified by:

setSampler in interface FeatureSelectLimitIntensity<Point>

getGridCell

protected FeatureSelectUniformBest.Info<Point> getGridCell(Point p)

Returns the grid cell that contains the point