IPSDK 0.2
IPSDK : Image Processing Software Development Kit
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) :

nearestNeighbors3d_shape_init.png

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

nearestNeighbors3d_shape.png

On previous figures :

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

nearestNeighbors3d_distribution.png

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
Geometry3d.png
Geometry 3d
none.png
None
parameter.png
NearestNeighbors3dMsrParams
Custom.png
Custom
BoundaryApproximation.png
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());