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SoAutoThresholdingQuantification Class

OIV.ImageViz.Engines.ImageAnalysis.Statistics.SoAutoThresholdingQuantification engine.

Inheritance Hierarchy

Namespace: OIV.ImageViz.Engines.ImageAnalysis.Statistics
Assembly: OIV.ImageViz (in OIV.ImageViz.dll) Version: 10.12.3.0 (10.12.3.0)
Syntax
public class SoAutoThresholdingQuantification : SoImageVizEngine

The SoAutoThresholdingQuantification type exposes the following members.

Constructors
  NameDescription
Public methodSoAutoThresholdingQuantification

Constructor.

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Methods
  NameDescription
Public methodAbortEvaluate

Abort current processing as soon as possible.

(Inherited from SoImageVizEngine.)
Public methodCopy

Creates and returns an exact copy of the engine.

(Inherited from SoEngine.)
Public methodCopyFieldValues(SoFieldContainer)
Calls CopyFieldValues(fc, false).
(Inherited from SoFieldContainer.)
Public methodCopyFieldValues(SoFieldContainer, Boolean)

Copies the contents of fc's fields into this object's fields.

(Inherited from SoFieldContainer.)
Public methodDispose
Releases all resources used by SoDisposable.
(Inherited from SoDisposable.)
Public methodEnableNotify

Notification at this Field Container is enabled (if flag == true) or disabled (if flag == false).

(Inherited from SoFieldContainer.)
Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Public methodFieldsAreEqual

Returns true if this object's fields are exactly equal to fc's fields.

(Inherited from SoFieldContainer.)
Public methodGet

Returns the values of the fields of this object in the Open Inventor ASCII file format in the given string.

(Inherited from SoFieldContainer.)
Public methodGetAllFields

Returns a list of fields, including the eventIn's and eventOut's.

(Inherited from SoFieldContainer.)
Public methodGetEventIn

Returns a the eventIn with the given name.

(Inherited from SoFieldContainer.)
Public methodGetEventOut

Returns the eventOut with the given name.

(Inherited from SoFieldContainer.)
Public methodGetField

Returns a the field of this object whose name is fieldName.

(Inherited from SoFieldContainer.)
Public methodGetFieldName

Returns the name of the given field in the fieldName argument.

(Inherited from SoFieldContainer.)
Public methodGetFields

Appends references to all of this object's fields to resultList, and returns the number of fields appended.

(Inherited from SoFieldContainer.)
Public methodGetHashCode
Overrides GetHashCode().
(Inherited from SoNetBase.)
Public methodGetName

Returns the name of an instance.

(Inherited from SoBase.)
Public methodGetOutput

Returns a reference to the engine output with the given name.

(Inherited from SoEngine.)
Public methodGetOutputName

Returns (in outputName) the name of the engine output (output).

(Inherited from SoEngine.)
Public methodGetOutputs

Returns a list of outputs in this engine.

(Inherited from SoEngine.)
Public methodGetStringName (Inherited from SoBase.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodHasDefaultValues

Returns true if all of the object's fields have their default values.

(Inherited from SoFieldContainer.)
Public methodIsEvaluating

Returns true if the engine evaluation is in progress.

(Inherited from SoImageVizEngine.)
Public methodIsNotifyEnabled

Notification is the process of telling interested objects that this object has changed.

(Inherited from SoFieldContainer.)
Public methodIsSynchronizable

Gets the ScaleViz synchronizable state of this object.

(Inherited from SoBase.)
Public methodSet

Sets one or more fields in this object to the values specified in the given string, which should be a string in the Open Inventor file format.

(Inherited from SoFieldContainer.)
Public methodSetName (Inherited from SoBase.)
Public methodSetSynchronizable

Sets this to be a ScaleViz synchronizable object.

(Inherited from SoBase.)
Public methodSetToDefaults

Sets all fields in this object to their default values.

(Inherited from SoFieldContainer.)
Public methodStartEvaluate

Evaluate engine and dependencies in another thread without blocking the current one.

(Inherited from SoImageVizEngine.)
Public methodToString
Converts this SoBase structure to a human readable string.
(Inherited from SoBase.)
Public methodTouch

Marks an instance as modified, simulating a change to it.

(Inherited from SoBase.)
Public methodWaitEvaluate

Wait for the end of engine evaluation.

(Inherited from SoImageVizEngine.)
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Properties
  NameDescription
Public propertycomputeMode

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

Public propertyinGrayImage

The input grayscale image Default value is NULL.

Public propertyintensityRangeInput
Public propertyIsDisposable
ISafeDisposable interface implementation.
(Inherited from SoDisposable.)
Public propertyoutResult

The thresholding results.

Public propertyrangeMode

The input intensity range.

Public propertythresholdCriterion

The criterion to detect thresholds on histogram.

Public propertyUserData
Gets or sets the user data to be contained by the field container.
(Inherited from SoFieldContainer.)
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Events
  NameDescription
Public eventOnBegin

Event raised when the processing begins.

(Inherited from SoImageVizEngine.)
Public eventOnEnd

Event raised when processing ends and the result is available.

(Inherited from SoImageVizEngine.)
Public eventOnProgress

Event raised while processing is running.

(Inherited from SoImageVizEngine.)
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Remarks

The OIV.ImageViz.Engines.ImageAnalysis.Statistics.SoAutoThresholdingQuantification engine extracts a value to automaticaly threshold on a gray level image.

Three methods of classification are available: Entropy, Factorisation or Moments. The computed threshold is provided in the OIV.ImageViz.Engines.ImageAnalysis.Statistics.SoAutoThresholdingQuantification.SbAutoThresholdingDetail object.

Entropy The entropy principle defines 2 classes in the image histogram by minimizing the total classes' entropy, for more theory the reader can refers to references [1] and [2]. Considering the first-order probability histogram of an image and assuming that all symbols in the flowing equation are statistically independent, its entropy (in the Shannon sense) is defined as:

Where is the number of grayscales, the probability of occurrence of level and is the log in base 2.

Let us denote the value of the threshold and the search interval. We can define two partial entropies:

Where defines the probability of occurrence of level in the range and defines the probability of occurrence of level in the range [t+1,I2]. We search the threshold value which minimizes the sum :

Figure 1: Example of thresholding using the entropy method

Factorization The factorization method is based on the Otsu criterion (see [3] for details), i.e. minimizing the within-class variance:

Where and are respectively the probabilities occurrence and , the variances of classes and .

A faster and equivalent approach is to maximize the between-class variance:

The within-class variance calculation is based on the second-order statistics (variances) while the between-class variance calculation is based on the first order statistics (means). It is therefore simplest and faster to use this last optimization criterion. We then search the value which maximizes the between-class variance such as:

Figure 2: Example of thresholding using the factorization method

Moments The moment OIV.ImageViz.Engines.ImageSegmentation.Binarization.SoAutoThresholdingProcessing uses the moment-preserving bi-level thresholding described by W.H.Tsai in [4]. Moments of an image can be computed from its histogram in the following way:

Where is the probability of occurrence of grayscale . For the following we note the original grayscale image and the threshold image. Image can be considered as a blurred version of an ideal bi-level image which consists of pixels with only two gray values: and . The moment-preserving thresholding principle is to select a threshold value such that if all below-threshold gray values of the original image are replaced by and all above threshold gray values replaced by , then the first three moments of the original image are preserved in the resulting bi-level image. Image so obtained may be regarded as an ideal unblurred version of . Let and denote the fractions of the below-threshold pixels and the above-threshold pixels in , respectively, then the first three moments of are:

And preserving the first three moments in , means the equalities:

To find the desired threshold value , we can first solve the four equations system to obtain and , and then choose as the -tile of the histogram of . Note that and will also be obtained simultaneously as part of the solutions of system.

Figure 3: Example of thresholding using the moment-preserving method

[1] T.Pun, Entropic thresholding: A new approach, comput. Graphics Image Process. 16, 1981, 210-239 [2] J. N. Kapur, P. K. Sahoo, and A. K. C. Wong, "A New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram" Computer Vision, Graphics and Image Processing 29, pp. 273-285, Mar. 1985 [3] Otsu, N. 1979. A thresholding selection method from grayscale histogram. IEEE Transactions on Systems, Man, and Cybernetics9(1): 62-66 [4] Tsai, W. H. 1985. Moment-preserving thresholding: A New Approach. Computer Vision, Graphics, and Image Processing 29: 377-393

FILE FORMAT/DEFAULT

AutoThresholdingQuantification {
computeMode MODE_AUTO
inGrayImage NULL
rangeMode MIN_MAX
intensityRangeInput 0.0f 255.0f
thresholdCriterion ENTROPY
}

Library references: auto_threshold_value

See Also