Distance to nearest neighbor 3dSee full documentation

computation of distance to nearest neighbor for each shape

This measure allows to compute the distance to the nearest neighbor for each shape. It is based on a geometric analysis of the shape neighborhood.

Meshes associated to shapes are currently extremely dense. In consequence the distance from a shape triangle to another shape is defined as minimum distance between its barycenter and the barycenters of the triangles of the other shape.

The parameter flag ProcessHoles allows to specify whether shape holes should be taken into account during the computation. Please see Distance to nearest neighbor 2d for an explanation of the effects of this flag.

Here is an example of the nearest neighbor computation for a single shape :

In the previous figure, the distance to the nearest neighbor is represented by a pink cone for the blue shape to the nearest shape belonging to its neighborhood.

Here is an example of the nearest neighbor computation for a sample of shapes :

In the previous figure, distance to the nearest neighbor is illustrated using a color map starting from green colors for lower distance and ending on red color for higher distances.

computation of distance to nearest neighbor for each shape

Measure synthesis :

Measure Type	Measure Unit Type	Parameter Type	Result Type	Shape Requirements
Geometry 3d	Length	DistanceToNearestNeighbor3dMsrParams	Value (ipsdk::ipReal64)	Boundary Approximation

See Shape measurement for additional information on these pictograms

Example of Python code :

Generic example in 3d case :

import PyIPSDK
import PyIPSDK.IPSDKIPLShapeAnalysis as shapeanalysis

    # Create the infoset
    inMeasureInfoSet3d = PyIPSDK.createMeasureInfoSet3d()
    PyIPSDK.createMeasureInfo(inMeasureInfoSet3d, "DistanceToNearestNeighbor3dMsr")
    
    #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("DistanceToNearestNeighbor3dMsr")
    
    # 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 pInGreyImg3d = loadTiffImageFile(inputGreyImgPath);

    // read entity shape 3d collection used for processing
    Shape3dCollPtr pShape3dColl = boost::make_shared<Shape3dColl>();
    IPSDK_REQUIRE(readFromBinaryFile(inputShape3dCollPath, *pShape3dColl) == true);

    // define a measure info set
    MeasureInfoSetPtr pMeasureInfoSet = MeasureInfoSet::create3dInstance();
    createMeasureInfo(pMeasureInfoSet, "DistanceToNearestNeighbor3dMsr", createHolesBasicPolicyMsrParams(bProcessHoles));
    
    // compute measure on shape 3d collection
    MeasureSetPtr pOutMeasureSet = shapeAnalysis3d(pInGreyImg3d, pShape3dColl, pMeasureInfoSet);

    // retrieve associated results
    const MeasureConstPtr& pDistanceToNearestNeighbor3dOutMsr = pOutMeasureSet->getMeasure("DistanceToNearestNeighbor3dMsr");
    const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64>& outResults = static_cast<const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64>&>(pDistanceToNearestNeighbor3dOutMsr->getMeasureResult());