SoGaussianGradientTensorProcessing2d Class Reference
[Edge Marking]

SoGaussianGradientTensorProcessing2d engine computes the structure tensor. More...

#include <ImageViz/Engines/EdgeDetection/EdgeMarking/SoGaussianGradientTensorProcessing2d.h>

Inheritance diagram for SoGaussianGradientTensorProcessing2d:

List of all members.

Public Member Functions
	SoGaussianGradientTensorProcessing2d ()
Public Attributes
SoSFImageDataAdapter	inImage
SoSFVec2f	standardDeviation
SoImageVizEngineOutput < SoSFImageDataAdapter, SoImageDataAdapter * >	outTensorImage

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Detailed Description

SoGaussianGradientTensorProcessing2d engine computes the structure tensor.

The SoGradientOperatorProcessing2d engine computes the structure tensor of the input image by convolving the input image with the square first order derivatives of a Gaussian Kernel.

For instance, , .

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

In order to extract the eigenvalues or vectors of the result image the SoEigenDecompositionProcessing2d command can be applied on the spectral image output.

SEE ALSO

SoEigenDecompositionProcessing2d, SoHessianMatrixProcessing2d, SoEigenvaluesToStructurenessProcessing2d.

FILE FORMAT/DEFAULT

GaussianGradientTensorProcessing2d {

inImage	NULL
standardDeviation	3.f 3.f

}

Library references: GaussianGradientTensor2d

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Constructor & Destructor Documentation

SoGaussianGradientTensorProcessing2d::SoGaussianGradientTensorProcessing2d

(

)

Constructor.

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Member Data Documentation

SoSFImageDataAdapter SoGaussianGradientTensorProcessing2d::inImage

inImage Default value is NULL.

Supported types include: grayscale color image.

SoImageVizEngineOutput<SoSFImageDataAdapter,SoImageDataAdapter*> SoGaussianGradientTensorProcessing2d::outTensorImage

outTensorImage Default value is NULL.

Supported types include: grayscale binary label color image.

SoSFVec2f SoGaussianGradientTensorProcessing2d::standardDeviation

The standard deviation for each direction (X, Y) 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 SbVec2f( 3.f, 3.f ).

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

• ImageViz/Engines/EdgeDetection/EdgeMarking/SoGaussianGradientTensorProcessing2d.h