image = fillHole3dImg (inBinImg3d)

Detailed Description

holes filling in a binary 3d image

This algorithm allows to fill holes inside connected components in an input binary image InBinImg3d with respect to a given neighborhood 3d policy (see 3d neighborhood models).

Two versions of this algorithm are implemented which can be selected using attribute InOptOptimizationPolicy which associated to enumerate ipsdk::imaproc::attr::eProcessingOptimizationPolicy :

a 'fast' version using a binary and a label intermediate image (which can optionally be provided via OutOptWk1BinImg and OutOptWk1LabelImg attributes)
a low memory consumption iterative algorithm which propagate reconstructed elements until convergence.

An example of hole filling algorithm is illustrated in 2d case : see Fill hole 2d.

Example of Python code :

Example imports

import PyIPSDK

import PyIPSDK.IPSDKIPLAdvancedMorphology as advmorpho

Code Example

    # opening of input image
    inBinImg3d = PyIPSDK.loadTiffImageFile(inputImgPath)
    
    # compute hole filling on input image
    outImg = advmorpho.fillHole3dImg(inBinImg3d)

Example of C++ code :

Example informations

Header file

#include <IPSDKIPL/IPSDKIPLAdvancedMorphology/Processor/FillHole3dImg/FillHole3dImg.h>

Code Example

    // opening input image
    ImagePtr pInBinImg3d = loadTiffImageFile(inputImgPath, eTiffDirectoryMode::eTDM_Volume, eTiffBufferMode::eTBM_Binary);
    // compute hole filling on input image
    ImagePtr pOutImg = fillHole3dImg(pInBinImg3d);