com.openinventor.imageviz.engines.imageanalysis.statistics

Class SoAutoThresholdingQuantification

java.lang.Object

com.openinventor.inventor.Inventor

com.openinventor.inventor.misc.SoBase

com.openinventor.inventor.fields.SoFieldContainer

com.openinventor.inventor.engines.SoEngine

com.openinventor.imageviz.engines.SoImageVizEngine

com.openinventor.imageviz.engines.imageanalysis.statistics.SoAutoThresholdingQuantification

All Implemented Interfaces:

SafeDisposable

public class SoAutoThresholdingQuantification
extends SoImageVizEngine

SoAutoThresholdingQuantification engine The 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 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

See also:

SoAutoThresholdingProcessing

File format/default:

AutoThresholdingQuantification {

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

}

Library references: auto_threshold_value

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SoAutoThresholdingQuantification.RangeModes
static class	SoAutoThresholdingQuantification.SbAutoThresholdingDetail Results details of threshold by automatic segmentation.
static class	SoAutoThresholdingQuantification.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
SoSFEnum<SoImageVizEngine.ComputeModes>	computeMode Select the compute Mode (2D or 3D or AUTO) .
static int	ENTROPY Deprecated. Use SoAutoThresholdingQuantification.ThresholdCriterions.ENTROPY instead.
static int	FACTORISATION Deprecated. Use SoAutoThresholdingQuantification.ThresholdCriterions.FACTORISATION instead.
SoSFImageDataAdapter	inGrayImage The input grayscale image Default value is NULL.
SoSFVec2f	intensityRangeInput The input intensity range used when rangeMode = OTHER.
static int	MIN_MAX Deprecated. Use SoAutoThresholdingQuantification.RangeModes.MIN_MAX instead.
static int	MOMENTS Deprecated. Use SoAutoThresholdingQuantification.ThresholdCriterions.MOMENTS instead.
static int	OTHER Deprecated. Use SoAutoThresholdingQuantification.RangeModes.OTHER instead.
SoImageVizEngineAnalysisOutput<SoAutoThresholdingQuantification.SbAutoThresholdingDetail>	outResult The thresholding results.
SoSFEnum<SoAutoThresholdingQuantification.RangeModes>	rangeMode The input intensity range.
SoSFEnum<SoAutoThresholdingQuantification.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
SoAutoThresholdingQuantification() Constructor.

Method Summary

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

MIN_MAX

@Deprecated
public static final int MIN_MAX

Deprecated. Use SoAutoThresholdingQuantification.RangeModes.MIN_MAX instead.

OTHER

@Deprecated
public static final int OTHER

Deprecated. Use SoAutoThresholdingQuantification.RangeModes.OTHER instead.

ENTROPY

@Deprecated
public static final int ENTROPY

Deprecated. Use SoAutoThresholdingQuantification.ThresholdCriterions.ENTROPY instead.

FACTORISATION

@Deprecated
public static final int FACTORISATION

Deprecated. Use SoAutoThresholdingQuantification.ThresholdCriterions.FACTORISATION instead.

MOMENTS

@Deprecated
public static final int MOMENTS

Deprecated. Use SoAutoThresholdingQuantification.ThresholdCriterions.MOMENTS instead.

computeMode

public final SoSFEnum<SoImageVizEngine.ComputeModes> computeMode

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

inGrayImage

public final SoSFImageDataAdapter inGrayImage

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

rangeMode

public final SoSFEnum<SoAutoThresholdingQuantification.RangeModes> rangeMode

The input intensity range. . Default is MIN_MAX

intensityRangeInput

public final SoSFVec2f intensityRangeInput

The input intensity range used when rangeMode = OTHER. Default value is SbVec2f(0.0f,255.0f).

thresholdCriterion

public final SoSFEnum<SoAutoThresholdingQuantification.ThresholdCriterions> thresholdCriterion

The criterion to detect thresholds on histogram. . Default is ENTROPY

outResult

public final SoImageVizEngineAnalysisOutput<SoAutoThresholdingQuantification.SbAutoThresholdingDetail> outResult

The thresholding results. Default value is NULL.

Constructor Detail

SoAutoThresholdingQuantification

public SoAutoThresholdingQuantification()

Constructor.