SoLocalMaximaQuantification Class Reference
[Statistics]

ImageViz SoLocalMaximaQuantification engine More...

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

Inheritance diagram for SoLocalMaximaQuantification:
SoImageVizEngine SoEngine SoFieldContainer SoBase SoRefCounter SoTypedObject

List of all members.

Classes

class  SbLocalMaximaDetail
 Results details of SoLocalMaximaQuantification. More...

Public Types

enum  PrecisionMode {
  PIXEL = 0,
  SUB_PIXEL = 1
}

Public Member Functions

 SoLocalMaximaQuantification ()

Public Attributes

SoSFEnum computeMode
SoSFImageDataAdapter inGrayImage
SoSFVec3i32 localWindow
SoSFFloat thresholdLevel
SoSFEnum precisionMode
SoSFInt32 numberOfPatterns
SoImageVizEngineAnalysisOutput
< SbLocalMaximaDetail
outResult

Detailed Description

ImageViz SoLocalMaximaQuantification engine

The SoLocalMaximaQuantification engine extracts the local maxima of an image using a neighborhood analysis.

Input_Image[i,j] is a local maximum if the 2 conditions below apply:

1. Considering k in [1,p], l in [1,q] and m in [-p,p], InputImage(i,j) verifies:
InputImage( i, j) > InputImage(i + m, j - l)
InputImage( i, j) > InputImage(i - k, j)
InputImage(i, j) InputImage(i + k, j)
InputImage(i, j) InputImage(i + m, j + l)

2. Input_Image[i,j] is higher than a specified threshold
InputImage(i, j) threshold

SoLocalMaximaQuantification_image01.png

Graphic visualization of the neighborhood analysis

Examples: Example 1:
Input parameters: p=0, q=0, threshold=4, number=50.
The local maxima will be the points higher or equal to 4.

SoLocalMaximaQuantification_image03.png

Number of local maxima detected: 7
Positions of the local maxima:
(7,3) (6,5) (5,7) (6,7) (6,8) (2,9) (6,9)
This corresponds to a threshold.

Example 2: Input parameters:p=1, q=1, threshold=3, number=50.
Number of local maxima detected: 4
Positions of the local maxima: (7,3) (6,5) (5,7) (2,9)

Remark: If there is an area in the image at constant level, the engine returns the upper left corner of this area. The other points of the area are not considered as �local maxima�.

SoLocalMaximaQuantification_image04.png

Example 3: Input parameters: p=2, q=2, threshold=3, number=50.
Number of local maxima detected: 2
Positions of the local maxima: (7,3) (5,7)

Remark: The algorithm is not performed on the image border depending on n and m values. That is the reason why the point (2,9) is not considered as a local maximum.

SoLocalMaximaQuantification_image05.png

Local Maximum Sub-Pixel Position Determination:
On example 3, the algorithm detects 2 local maxima. The positions are converted to sub-pixel positions:

SoLocalMaximaQuantification_image06.png

X Sub-pixel Position Determined by Parabola Approximation

SoLocalMaximaQuantification_image07.png

Y Sub-pixel Position Determined by Parabola Approximation

SoLocalMaximaQuantification_image08.png

FILE FORMAT/DEFAULT


Library references: maxextract maxextract3d


Member Enumeration Documentation

Enumerator:
PIXEL 
SUB_PIXEL 

Constructor & Destructor Documentation

SoLocalMaximaQuantification::SoLocalMaximaQuantification (  ) 

Constructor.


Member Data Documentation

Select the compute Mode (2D or 3D or AUTO) Use enum ComputeMode.

Default is MODE_AUTO

Enter input grey level image Default value is NULL.

Supported types include: grayscale binary label image.

The neighborhood size in X, Y and Z.

Default value is SbVec3i32(3,3,3).

The number of patterns to be detected.

Default value is 1.

The matching results.

Default value is NULL.

Select the precision mode of position.

Use enum PrecisionMode. Default is PIXEL

Threshold.

Default value is 0.0f.


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

Open Inventor Toolkit reference manual, generated on 17 Dec 2019
Copyright © Thermo Fisher Scientific All rights reserved.
http://www.openinventor.com/