SoSupervisedTextureClassificationProcessing2d Class Reference
[Classification]

ImageViz SoSupervisedTextureClassificationProcessing2d engine More...

#include <ImageViz/Engines/ImageSegmentation/Classification/SoSupervisedTextureClassificationProcessing2d.h>

Inheritance diagram for SoSupervisedTextureClassificationProcessing2d:
SoImageVizEngine SoEngine SoFieldContainer SoBase SoRefCounter SoTypedObject

List of all members.

Public Types

enum  FeatureGroup {
  DIRECTIONNAL_COOCCURRENCE = 1,
  ROTATION_INVARIANT_COOCCURRENCE = 2,
  FIRST_ORDER_STATISTICS = 4,
  HISTOGRAM_STATISTICS = 8,
  INTENSITY = 16
}
enum  CoocTextonShape {
  CUBE = 0,
  SPHERE = 1,
  BALL = 2
}
enum  OutMapType {
  CLOSEST_DISTANCE = 0,
  RELATIVE_DISTANCE = 1,
  CLASS_DISTANCE = 2,
  NONE = 3
}

Public Member Functions

 SoSupervisedTextureClassificationProcessing2d ()

Public Attributes

SoSFImageDataAdapter inImage
SoSFImageDataAdapter inTrainingImage
SoSFBitMask featureGroup
SoSFVec2i32 radiusRange
SoSFUInt32 radiusStep
SoSFUInt32 coocRadius
SoSFEnum coocTextonShape
SoSFUInt32 coocTextonSize
SoSFDouble minSeparationPercentage
SoImageVizEngineOutput
< SoSFImageDataAdapter,
SoImageDataAdapter * > 
outLabelImage
SoSFEnum outMapType
SoImageVizEngineOutput
< SoSFImageDataAdapter,
SoImageDataAdapter * > 
outMapImage

Detailed Description

ImageViz SoSupervisedTextureClassificationProcessing2d engine

The SoSupervisedTextureClassificationProcessing3d engine realizes a segmentation based on a texture model automatically built from a training input image.

It chains automatically the 3 steps of the texture classification workflow: model creation, texture model learning and model application.

For an introduction see the Texture classification section

FILE FORMAT/DEFAULT


Library references: SupervisedTextureClassification2D


Member Enumeration Documentation

This enum defines all type of measures used for texture classification.

Enumerator:
CUBE 

The set of all points associated to corners, middles of edges and middles of faces of a cube of size textonSize.

SPHERE 

The set of all points situated at the same euclidean distance textonSize from the center.

This mode must be used when a repetitive texture is mono-scale.

BALL 

The set of all points situated at a distance less or equal to textonSize from the center.

This mode can be useful to classify a multi-scale repetitive texture but may be very time consuming.

This enum defines all type of measures used for texture classification.

Enumerator:
DIRECTIONNAL_COOCCURRENCE 

Features based on co-occurrence's matrix.

One feature is extracted from each co-occurrence vector.

ROTATION_INVARIANT_COOCCURRENCE 

Features based on co-occurrence's matrix.

3 statistics features are extracted from all vectors.

FIRST_ORDER_STATISTICS 

Features based on first order statistics which are not computed using an histogram.

HISTOGRAM_STATISTICS 

Features based on histogram statistics.

INTENSITY 

Feature based on the intensity value of the input image.

Enumerator:
CLOSEST_DISTANCE 

The outMapImage represents the mahalanobis distance to the class selected by the classification.

The closer to 0 this metric is, the more confident the classification is.

RELATIVE_DISTANCE 

The outMapImage represents the mahalanobis distance to the class selected by the classification( d1 ) weighted by the gap with the second closest distance( d2 ).

The smaller this metric is, the more confident and less ambiguous the classification is. Map Value = log( d1 / ( d2 - d1 ) ).

CLASS_DISTANCE 

The outMapImage is a multichannel image where each channel represents the distance to the corresponding class.

NONE 

No output map.


Constructor & Destructor Documentation

SoSupervisedTextureClassificationProcessing2d::SoSupervisedTextureClassificationProcessing2d (  ) 

Constructor.


Member Data Documentation

Radius of the circular neighborhood used by the cooccurrence features.

Default value is 10.

The shape of the co-occurrence texton, i.e., the pattern defined by the set of co-occurrence vectors.

This shape represents the distribution of points around the target point for computing the co-occurrence matrix. The shape, associated to the texton size, defines the set of vectors that are used for computing co-occurrence features. For instance, in 2D, a Cube shape of size 3 defines the co-occurrence vectors (-3, -3) , (0, -3), (3, -3), (-3, 0) , (3, 0), (-3, 3) , (0, 3) and (3, 3). This parameter is ignored if none of the co-occurrence measure types is selected. Use enum CoocTextonShape. Default is SPHERE

The size of the texton shape for co-occurrence features.

This size is constrained by the radius parameter. The constraint depends on the texton shape. For instance, with a square texton, the texton size cannot exceed the rounded value of

\[ radius \times \sqrt{2} \]

. This parameter is ignored if none of the co-occurrence measure types is selected. Default value is 4.

The groups of textural features to compute.

Use enum FeatureGroup. Default is DIRECTIONNAL_COOCCURRENCE | ROTATION_INVARIANT_COOCCURRENCE | FIRST_ORDER_STATISTICS | HISTOGRAM_STATISTICS | INTENSITY

The input grayscale image to segment.

Default value is NULL. Supported types include: grayscale image.

The input label training image (16 or 32 bits).

Each label represents a class sample for the learning step. Default value is NULL. Supported types include: label image.

This parameter controls the rejection criteria of the feature selection algorithm (FS).

A measure is rejected if its contribution does not increase enough the separation power of the classification model. This ratio indicates the minimal relative growth required to keep a measure. Please refer to Feature Selection section for more information about this parameter. The value must be greater than or equal to 0.0. Default value is 3.0.

The output label image representing the texture classification result.

Default value is NULL. Supported types include: label image.

Output map image.

The type of the image will be float. Default value is NULL. Supported types include: grayscale binary label color image.

The Output map image type.

Default is CLOSEST_DISTANCE. Use enum OutMapType. Default is CLOSEST_DISTANCE

The minimum and maximum radius of the circular neighborhoods used for computing textural features.

Default value is SbVec2i32(2,14).

The step used to define the set of radius between minimum and maximum.

The maximum radius is systematically added to the radius list. Default value is 4.


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

Open Inventor Toolkit reference manual, generated on 28 Oct 2019
Copyright © Thermo Fisher Scientific All rights reserved.
http://www.openinventor.com/