public class LikelihoodHistCoupled_SB_U8 extends java.lang.Object implements PixelLikelihood<boofcv.struct.image.GrayU8>
Creates a histogram in a gray scale image which is then used to compute the likelihood of a color being a member of the original distribution based on its frequency.
Design Note:
The reason operations in GHistogramFeatureOps is not used internally is because
those are for histograms stored in double arrays, while this has to use floats/
| Constructor and Description |
|---|
LikelihoodHistCoupled_SB_U8(int maxPixelValue,
int numBins) |
| Modifier and Type | Method and Description |
|---|---|
float |
compute(int x,
int y) |
void |
createModel(georegression.struct.shapes.RectangleLength2D_I32 target)
Specifies where the initial location of the target is in the image and computes the model using pixels
inside the rectangle
|
boolean |
isInBounds(int x,
int y) |
void |
setImage(boofcv.struct.image.GrayU8 image)
Sets the input image
|
public LikelihoodHistCoupled_SB_U8(int maxPixelValue,
int numBins)
public void setImage(boofcv.struct.image.GrayU8 image)
PixelLikelihoodsetImage in interface PixelLikelihood<boofcv.struct.image.GrayU8>setImage in interface boofcv.struct.sparse.SparseImageOperator<boofcv.struct.image.GrayU8>public boolean isInBounds(int x,
int y)
isInBounds in interface boofcv.struct.sparse.SparseImageOperator<boofcv.struct.image.GrayU8>public void createModel(georegression.struct.shapes.RectangleLength2D_I32 target)
PixelLikelihoodcreateModel in interface PixelLikelihood<boofcv.struct.image.GrayU8>target - Location of target inside the imagepublic float compute(int x,
int y)
compute in interface boofcv.struct.sparse.SparseImageSample_F32<boofcv.struct.image.GrayU8>