Local histogram module

Measure allowing to compute Lowitz local histogram module. More...

Classes
class	ipsdk::imaproc::shape::analysis::LocalHistogramModuleMsr
	Measurement object for measure LocalHistogramModule. More...
class	ipsdk::imaproc::shape::analysis::LocalHistogramModuleMsrInfo
	Information object for measure LocalHistogramModule. More...
class	ipsdk::imaproc::shape::analysis::LocalHistogramModuleMsrParams
	Parameter object for measure LocalHistogramModule. More...

Detailed Description

Measure allowing to compute Lowitz local histogram module.

This measure computes the local histogram module [1], of image pixel/voxel intensity values associated to a 2d/3d shape. The higher is the measure, the more homogeneous is the shape. Homogeneous shapes yields 1/NumericLimits<ipReal64>::epsilon().

This measure is based on the analysis of the shape histogram (see Histogram). Given the histogram parameters allowing to determine (among others) the number of classes and a global range for the histogram, this measure is computed as the Mahalanobis distance between the actual histogram and the theoretical histogram for which each bin has the same value. This distance can be expressed as :

Where is the number of classes in the histogram, is the expected value of the bin of the histogram and is its variance.

Let us define as the value of the normalized histogram : , with being the number of pixels in the shape. Since this measure is based on Bernoulli distribution, the expected value of and its variance are :

Moreover the expected value (and hence probability) and variance of the theoretical histogram for each bin are:

With draws (1 per pixel in the shape), we can rewrite the Mahalanobis distance as follows :

Here is an example of energy measurement in 2d case :

References

[1] G. Lowitz "Can a Local Histogram Really Map Texture Information?". Pattern Recognition, 16, 2, 1983, pp 141–147.

Author

R. Abbal

Date

2017/02/27

Copyright

2017 Reactiv'IP, all right reserved.

Measure allowing to compute Lowitz local histogram module

Measure synthesis :

Measure Type	Measure Unit Type	Parameter Type	Result Type	Shape Requirements
Generic	None	LocalHistogramModuleMsrParams	Value (ipsdk::ipReal64)	Row Intersections

See Shape measurement for additional information on these pictograms

Measure Type :

This is a generic measure

• it does not directly use shape or image data
• it can use dependencies to other measures to compute a result (see Measure Dependencies section)

This measure can be used in 2d and 3d case

Measure Unit Type:

Measure LocalHistogramModule is not associated to any unit [ipsdk::shape::analysis::eMsrUnitFormat::eMUF_NoUnit]

Measure Parameter Type :

Measure LocalHistogramModule is associated to LocalHistogramModuleMsrParams parameters

Measure Result Type :

Measure LocalHistogramModule is associated to ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64> results

Measure Shape Requirements :

Measure LocalHistogramModule requires row intersections from shape data

Measure Dependencies :

Measure LocalHistogramModule depends on following measures :

Measure Mode	Measure Name	Measure Type	Measure Parameters
eMVP_2d3d	Histogram	Histogram	createHistogramMsrParams(_pMsrParams->getNode<LocalHistogramModuleMsrParams::HistoParams>())

Note

See Shape Analysis 2d for more information on general shape 2d analysis and measurement usage.

See Shape Analysis 3d for more information on general shape 3d analysis and measurement usage.

Example of Python code :

Generic example in 2d case :

import PyIPSDK
import PyIPSDK.IPSDKIPLShapeAnalysis as shapeanalysis

    # Create the infoset
    inMeasureInfoSet2d = PyIPSDK.createMeasureInfoSet2d()
    PyIPSDK.createMeasureInfo(inMeasureInfoSet2d, "LocalHistogramModuleMsr")
    
    #Perform the analysis
    outMeasureSet = shapeanalysis.labelAnalysis2d(inGreyImg, inLabelImg2d, inMeasureInfoSet2d)
    
    # save results to csv format
    PyIPSDK.saveCsvMeasureFile(os.path.join(tmpPath,  "shape_analysis_results.csv"), outMeasureSet)
    
    # retrieve measure results
    outMsr = outMeasureSet.getMeasure("LocalHistogramModuleMsr")
    
    # retrieve measure values
    outMsrValues = outMsr.getMeasureResult().getColl(0)
    print("First label measurement equal " + str(outMsrValues[1]))

Generic example in 3d case :

import PyIPSDK
import PyIPSDK.IPSDKIPLShapeAnalysis as shapeanalysis

    # Create the infoset
    inMeasureInfoSet3d = PyIPSDK.createMeasureInfoSet3d()
    PyIPSDK.createMeasureInfo(inMeasureInfoSet3d, "LocalHistogramModuleMsr")
    
    #Perform the analysis
    outMeasureSet = shapeanalysis.labelAnalysis3d(inGreyImg, inLabelImg, inMeasureInfoSet3d)
    
    # save results to csv format
    PyIPSDK.saveCsvMeasureFile(os.path.join(tmpPath,  "shape_analysis_results.csv"), outMeasureSet)
    
    # retrieve measure results
    outMsr = outMeasureSet.getMeasure("LocalHistogramModuleMsr")
    
    # retrieve measure values
    outMsrValues = outMsr.getMeasureResult().getColl(0)
    print("First label measurement equal " + str(outMsrValues[1]))

Example of C++ code :

Example informations

Associated library

IPSDKIPLShapeAnalysis

Code Example

    // opening grey level input image
    ImagePtr pInGreyImg2d = loadTiffImageFile(inputGreyImgPath);

    // read entity shape 2d collection used for processing
    Shape2dCollPtr pShape2dColl = boost::make_shared<Shape2dColl>();
    IPSDK_REQUIRE(readFromXmlFile(inputShape2dCollPath, *pShape2dColl) == true);

    // define a measure info set
    MeasureInfoSetPtr pMeasureInfoSet = MeasureInfoSet::create2dInstance();
    createMeasureInfo(pMeasureInfoSet, "LocalHistogramModuleMsr");
    
    // compute measure on shape 2d collection
    MeasureSetPtr pOutMeasureSet = shapeAnalysis2d(pInGreyImg2d, pShape2dColl, pMeasureInfoSet);

    // retrieve associated results
    const MeasureConstPtr& pLocalHistogramModuleOutMsr = pOutMeasureSet->getMeasure("LocalHistogramModuleMsr");
    const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64>& outResults = static_cast<const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64>&>(pLocalHistogramModuleOutMsr->getMeasureResult());