Nearest neighbors 3dSee full documentation

measure allowing to retrieve shapes at a given distance of measured shape

This measure allows to collect index and distance of neighbors of a shape given a user parameter distance threshold MaxDist (we collect shape indexes for which distance is lower or equal to this value). It is based on a geometric analysis of shape neighborhood.

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

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

Given an input shape (in blue) with neighbors (in grey) :

We collect indexes of neighbors at a given distance of considered shape :

On previous figures :

• yellow wireframe represents the isosurface at given distance of shape (so we keep neighbor shapes with intersection with this volume)
• green shapes are shape for which associated distance is lower or equal to requested distance
• red shapes are associated to a distance greater than requested distance an will be excluded

Here is an example of number of nearest neighbors computation for a sample of shapes :

On previous figure, number of collected nearest neighbors is illustrated using a color map starting on green colors for fewer number of neighbors and ending on red color for higher number of neighbors.

measure allowing to retrieve shapes at a given distance of measured shape

Measure synthesis :

Measure Type	Measure Unit Type	Parameter Type	Result Type	Shape Requirements
Geometry 3d	None	NearestNeighbors3dMsrParams	Custom	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, "NearestNeighbors3dMsr")
    
    #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("NearestNeighbors3dMsr")
    
    # 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, eTiffDirectoryMode::eTDM_Volume);

    // 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, "NearestNeighbors3dMsr", createNeighborsDistanceMsrParams(maxDist, bProcessHoles));
    
    // compute measure on shape 3d collection
    MeasureSetPtr pOutMeasureSet = shapeAnalysis3d(pInGreyImg3d, pShape3dColl, pMeasureInfoSet);

    // retrieve associated results
    const MeasureConstPtr& pNearestNeighbors3dOutMsr = pOutMeasureSet->getMeasure("NearestNeighbors3dMsr");
    const NearestNeighborsMsrResults& outResults = static_cast<const NearestNeighborsMsrResults&>(pNearestNeighbors3dOutMsr->getMeasureResult());