Open Inventor 9.9
com.openinventor.imageviz.engines.imagesegmentation.binarization

## Class SoAutoThresholdingProcessing

• All Implemented Interfaces:
SafeDisposable

```public class SoAutoThresholdingProcessing
extends SoImageVizEngine```
`SoAutoThresholdingProcessing` engine The `SoAutoThresholdingProcessing` engine computes an automatic threshold on a gray level image.

This engine computes an automatic threshold on a grayscale image i.e. separate the image in 2 classes of pixels. Three methods of classification are available: Entropy, Factorisation or Moments. The computed threshold is provided in the `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 `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:

AutoThresholdingProcessing {

 computeMode MODE_AUTO objectLightness BRIGHT_OBJECTS inGrayImage NULL intensityRangeInput 0.0f 255.0f thresholdCriterion ENTROPY rangeMode MIN_MAX
}

Library references: auto_threshold auto_threshold_inv

• ### Nested Class Summary

Nested Classes
Modifier and Type Class and Description
`static class ` `SoAutoThresholdingProcessing.ObjectLightnessType`
`static class ` `SoAutoThresholdingProcessing.RangeModes`
`static class ` `SoAutoThresholdingProcessing.SbAutoThresholdingDetail`
Results details of threshold by automatic segmentation.
`static class ` `SoAutoThresholdingProcessing.ThresholdCriterions`
• ### Nested classes/interfaces inherited from class com.openinventor.imageviz.engines.SoImageVizEngine

`SoImageVizEngine.ComputeModes, SoImageVizEngine.EventArg, SoImageVizEngine.Neighborhood3ds`
• ### Nested classes/interfaces inherited from class com.openinventor.inventor.Inventor

`Inventor.ConstructorCommand`
• ### Field Summary

Fields
Modifier and Type Field and Description
`static int` `BRIGHT_OBJECTS`
Deprecated.
`SoSFEnum<SoImageVizEngine.ComputeModes>` `computeMode`
Select the compute Mode (2D or 3D or AUTO) .
`static int` `DARK_OBJECTS`
Deprecated.
`static int` `ENTROPY`
Deprecated.
`static int` `FACTORISATION`
Deprecated.
`SoSFImageDataAdapter` `inGrayImage`
The input grayscale image.
`SoSFVec2f` `intensityRangeInput`
The input intensity range.
`static int` `MIN_MAX`
Deprecated.
`static int` `MOMENTS`
Deprecated.
`SoSFEnum<SoAutoThresholdingProcessing.ObjectLightnessType>` `objectLightness`
Select the lightness mode for object to detect.
`static int` `OTHER`
Deprecated.
`SoImageVizEngineOutput<SoSFImageDataAdapter,SoImageDataAdapter>` `outBinaryImage`
The output binary image.
`SoImageVizEngineAnalysisOutput<SoAutoThresholdingProcessing.SbAutoThresholdingDetail>` `outResult`
The thresholding results.
`SoSFEnum<SoAutoThresholdingProcessing.RangeModes>` `rangeMode`
Select the input intensity range mode.
`SoSFEnum<SoAutoThresholdingProcessing.ThresholdCriterions>` `thresholdCriterion`
The criterion to detect thresholds on histogram.
• ### Fields inherited from class com.openinventor.imageviz.engines.SoImageVizEngine

`CONNECTIVITY_18, CONNECTIVITY_26, CONNECTIVITY_6, MODE_2D, MODE_3D, MODE_AUTO, onBegin, onEnd, onProgress`
• ### Fields inherited from class com.openinventor.inventor.Inventor

`VERBOSE_LEVEL, ZeroHandle`
• ### Constructor Summary

Constructors
Constructor and Description
`SoAutoThresholdingProcessing()`
Constructor.

• ### Methods inherited from class com.openinventor.imageviz.engines.SoImageVizEngine

`abortEvaluate, isEvaluating, startEvaluate, waitEvaluate`
• ### Methods inherited from class com.openinventor.inventor.engines.SoEngine

`copy, getByName, getOutput, getOutputName`
• ### Methods inherited from class com.openinventor.inventor.fields.SoFieldContainer

`copyFieldValues, copyFieldValues, enableNotify, fieldsAreEqual, get, getAllFields, getEventIn, getEventOut, getField, getFieldName, hasDefaultValues, isNotifyEnabled, set, setToDefaults`
• ### Methods inherited from class com.openinventor.inventor.misc.SoBase

`dispose, getEXTERNPROTO, getName, getPROTO, isDisposable, isSynchronizable, setName, setSynchronizable, touch`
• ### Methods inherited from class com.openinventor.inventor.Inventor

`getAddress, getNativeResourceHandle, startInternalThreads, stopInternalThreads`
• ### Methods inherited from class java.lang.Object

`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Field Detail

• #### BRIGHT_OBJECTS

```@Deprecated
public static final int BRIGHT_OBJECTS```
Deprecated.
• #### DARK_OBJECTS

```@Deprecated
public static final int DARK_OBJECTS```
Deprecated.
• #### ENTROPY

```@Deprecated
public static final int ENTROPY```
Deprecated.
• #### FACTORISATION

```@Deprecated
public static final int FACTORISATION```
Deprecated.
• #### MOMENTS

```@Deprecated
public static final int MOMENTS```
Deprecated.
• #### MIN_MAX

```@Deprecated
public static final int MIN_MAX```
Deprecated.
• #### OTHER

```@Deprecated
public static final int OTHER```
Deprecated.
• #### computeMode

`public final SoSFEnum<SoImageVizEngine.ComputeModes> computeMode`
Select the compute Mode (2D or 3D or AUTO) . Default is MODE_AUTO
• #### objectLightness

`public final SoSFEnum<SoAutoThresholdingProcessing.ObjectLightnessType> objectLightness`
Select the lightness mode for object to detect. . Default is BRIGHT_OBJECTS
• #### inGrayImage

`public final SoSFImageDataAdapter inGrayImage`
The input grayscale image. Default value is NULL. Supported types include: grayscale image.
• #### intensityRangeInput

`public final SoSFVec2f intensityRangeInput`
The input intensity range. Default value is `SbVec2f`(0.0f,255.0f).
• #### thresholdCriterion

`public final SoSFEnum<SoAutoThresholdingProcessing.ThresholdCriterions> thresholdCriterion`
The criterion to detect thresholds on histogram. . Default is ENTROPY
• #### rangeMode

`public final SoSFEnum<SoAutoThresholdingProcessing.RangeModes> rangeMode`
Select the input intensity range mode. . Default is MIN_MAX
• #### outBinaryImage

`public final SoImageVizEngineOutput<SoSFImageDataAdapter,SoImageDataAdapter> outBinaryImage`
The output binary image. Default value is NULL. Supported types include: binary image.
• #### outResult

`public final SoImageVizEngineAnalysisOutput<SoAutoThresholdingProcessing.SbAutoThresholdingDetail> outResult`
The thresholding results. Default value is NULL.
• ### Constructor Detail

• #### SoAutoThresholdingProcessing

`public SoAutoThresholdingProcessing()`
Constructor.