SoGaussianGradientTensorProcessing3d Class Reference
[Edge Marking]

ImageViz SoGaussianGradientTensorProcessing3d engine computes the structure tensor. More...

#include <ImageViz/Engines/EdgeDetection/EdgeMarking/SoGaussianGradientTensorProcessing3d.h>

Inheritance diagram for SoGaussianGradientTensorProcessing3d:
SoImageVizEngine SoEngine SoFieldContainer SoBase SoRefCounter SoTypedObject

List of all members.

Public Member Functions

 SoGaussianGradientTensorProcessing3d ()

Public Attributes

SoSFImageDataAdapter inImage
SoSFVec3f standardDeviation
SoImageVizEngineOutput
< SoSFImageDataAdapter,
SoImageDataAdapter * > 
outTensorImage

Detailed Description

ImageViz SoGaussianGradientTensorProcessing3d engine computes the structure tensor.

The SoGradientOperatorProcessing3d engine computes the structure tensor of the input image $\begin{pmatrix} I_x.I_x & I_x.I_y & I_x.I_z\\ I_x.I_y & I_y.I_y & I_y.I_z\\ I_x.I_z & I_y.I_z & I_z.I_z \end{pmatrix} = \begin{pmatrix} I_x\\ I_y\\ I_z \end{pmatrix} \cdot \begin{pmatrix} I_x & I_y & I_z\end{pmatrix}$ by convolving the input image with the square first order derivatives of a Gaussian Kernel.

For instance, $I_x = \frac{\partial I}{\partial x}$, $I_y = \frac{\partial I}{\partial x}$, $I_z = \frac{\partial I}{\partial z}$.

This filter provides an output spectral image where each channel represents a product of two partial derivative set in the following order $I_x.I_x$, $I_x.I_y$, $I_x.I_z$, $I_y.I_y$, $I_y.I_z$, $I_z.I_z$.

In order to extract the eigenvalues or vectors of the result image the SoEigenDecompositionProcessing3d command can be applied on the spectral image output.

SEE ALSO

SoEigenDecompositionProcessing3d, SoHessianMatrixProcessing3d, SoEigenvaluesToStructurenessProcessing3d.

FILE FORMAT/DEFAULT


Library references: GaussianGradientTensor3d


Constructor & Destructor Documentation

SoGaussianGradientTensorProcessing3d::SoGaussianGradientTensorProcessing3d (  ) 

Constructor.


Member Data Documentation

inImage Default value is NULL.

Supported types include: grayscale color image.

outTensorImage Default value is NULL.

Supported types include: grayscale binary label color image.

The standard deviation for each direction (X, Y, Z) of the Gaussian Kernel that is used for computing first order derivatives.

Each value must be greater than or equal to 0.1. Default value is SbVec3f( 3.f, 3.f, 3.f ).


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

Open Inventor Toolkit reference manual, generated on 15 Mar 2023
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