SoCooccurrenceQuantification2d Class Reference
[Statistics]

ImageViz SoCooccurrenceQuantification2d engine provides texture indicators based on the co-occurrence matrix computation. More...

#include <ImageViz/Engines/ImageAnalysis/Statistics/SoCooccurrenceQuantification2d.h>

Inheritance diagram for SoCooccurrenceQuantification2d:

List of all members.

Classes

class  SbCoocurrrenceDetail
 Results details of cooccurrence global measure. More...

Public Member Functions

 SoCooccurrenceQuantification2d ()

Public Attributes

SoSFImageDataAdapter inImage
SoSFImageDataAdapter inMaskImage
SoSFInt32 offsetX
SoSFInt32 offsetY
SoImageVizEngineAnalysisOutput
< SbCoocurrrenceDetail
outResult

Detailed Description

ImageViz SoCooccurrenceQuantification2d engine provides texture indicators based on the co-occurrence matrix computation.

The SoCooccurrenceQuantification2d engine provides some information concerning the texture thanks to the computation of a co-occurrence matrix. This command allow s to classify, given a direction $(dx,dy)$, pairs of pixels by their gray level. The co-occurrence matrix components are given by :

\[M(i,j)=number\left(\{x,y\}/(I(x,y)=i)\cap(I(x+dx,y+dy)=j)\right)\]

Where $I(x,y)$ is the image graylevel for $(x,y)$ coordinates.
This formulation means that for a given pair $(i,j)$, $M(i,j)$ contains the number of pixels verifying $I(x,y)=i$ and $I(x+dx,y+dy)=j$.

This matrix is made symmetric and normalized such as :

\[\forall(i,j),M(i,j)=M(j,i) ~\mbox{and} \sum_{i,j=1}^{N}M(i,j)=1\]

These operations allow to be independent to the image size and to hold properties on a direction and its symmetric. Thirteen indicators are computed from this matrix :

In addition this engine returns one more information in the result object which is the number of image pixels used for computation.

References

FILE FORMAT/DEFAULT


Library references: cooccurrence


Constructor & Destructor Documentation

SoCooccurrenceQuantification2d::SoCooccurrenceQuantification2d (  ) 

Constructor.


Member Data Documentation

The input image.

Default value is NULL. Supported types include: grayscale binary label color image.

The binary image for the mask or empty (command looks for only inside).

This parameter is optional. Default value is NULL. Supported types include: binary color image.

The X Offset.

Default value is 1.

The Y Offset.

Default value is 0.

The output measure result.

Default value is NULL.


The documentation for this class was generated from the following file:

Open Inventor Toolkit reference manual, generated on 22 Jan 2025
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