ImageDev

Dilation3d

Performs a three-dimensional dilation using a structuring element matching with a full or partial cube.

Access to parameter description

For an introduction: The dilation is performed by an iterative method in which each step dilates the result of the previous step. The kernelRadius parameter tunes the number of iterations, which sets the kernel size.
This algorithm uses a basic structuring element with 6, 18 or 26 neighbors, according to the neighborhood parameter.

<b> Figure 1.</b> Structuring elements: 6, 18 and 26 neighbors
Figure 1. Structuring elements: 6, 18 and 26 neighbors
See also

Function Syntax

This function returns outputImage. 
// Function prototype
std::shared_ptr< iolink::ImageView >
dilation3d( std::shared_ptr< iolink::ImageView > inputImage,
            uint32_t kernelRadius,
            Dilation3d::Neighborhood neighborhood,
            std::shared_ptr< iolink::ImageView > outputImage = NULL );
This function returns outputImage. 
// Function prototype.
dilation_3d( input_image,
             kernel_radius = 3,
             neighborhood = Dilation3d.Neighborhood.CONNECTIVITY_26,
             output_image = None )
This function returns outputImage. 
// Function prototype.
public static IOLink.ImageView
Dilation3d( IOLink.ImageView inputImage,
            UInt32 kernelRadius = 3,
            Dilation3d.Neighborhood neighborhood = ImageDev.Dilation3d.Neighborhood.CONNECTIVITY_26,
            IOLink.ImageView outputImage = null );

Class Syntax

Parameters

Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. The image type can be integer or float. Image Binary, Label, Grayscale or Multispectral nullptr
input
kernelRadius
The number of iterations (the half size of the structuring element, in voxels). A cube structuring element always has an odd side length (3x3x3, 5x5x5, etc.) which is defined by twice the kernel radius + 1. UInt32 >=1 3
input
neighborhood
The 3D neighborhood configuration.
CONNECTIVITY_6 The structuring element is composed of voxels with a common face with the voxel of interest.
CONNECTIVITY_18 The structuring element is composed of voxels with at least one common edge.
CONNECTIVITY_26 The structuring element is a full cube.
Enumeration CONNECTIVITY_26
output
outputImage
The output image. Its dimensions and type are forced to the same values as the input image. Image nullptr
Parameter Name Description Type Supported Values Default Value
input
input_image
The input image. The image type can be integer or float. image Binary, Label, Grayscale or Multispectral None
input
kernel_radius
The number of iterations (the half size of the structuring element, in voxels). A cube structuring element always has an odd side length (3x3x3, 5x5x5, etc.) which is defined by twice the kernel radius + 1. uint32 >=1 3
input
neighborhood
The 3D neighborhood configuration.
CONNECTIVITY_6 The structuring element is composed of voxels with a common face with the voxel of interest.
CONNECTIVITY_18 The structuring element is composed of voxels with at least one common edge.
CONNECTIVITY_26 The structuring element is a full cube.
enumeration CONNECTIVITY_26
output
output_image
The output image. Its dimensions and type are forced to the same values as the input image. image None
Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. The image type can be integer or float. Image Binary, Label, Grayscale or Multispectral null
input
kernelRadius
The number of iterations (the half size of the structuring element, in voxels). A cube structuring element always has an odd side length (3x3x3, 5x5x5, etc.) which is defined by twice the kernel radius + 1. UInt32 >=1 3
input
neighborhood
The 3D neighborhood configuration.
CONNECTIVITY_6 The structuring element is composed of voxels with a common face with the voxel of interest.
CONNECTIVITY_18 The structuring element is composed of voxels with at least one common edge.
CONNECTIVITY_26 The structuring element is a full cube.
Enumeration CONNECTIVITY_26
output
outputImage
The output image. Its dimensions and type are forced to the same values as the input image. Image null

Object Examples

auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" );

Dilation3d dilation3dAlgo;
dilation3dAlgo.setInputImage( foam );
dilation3dAlgo.setKernelRadius( 3 );
dilation3dAlgo.setNeighborhood( Dilation3d::Neighborhood::CONNECTIVITY_26 );
dilation3dAlgo.execute();

std::cout << "outputImage:" << dilation3dAlgo.outputImage()->toString();

foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip"))

dilation_3d_algo = imagedev.Dilation3d()
dilation_3d_algo.input_image = foam
dilation_3d_algo.kernel_radius = 3
dilation_3d_algo.neighborhood = imagedev.Dilation3d.CONNECTIVITY_26
dilation_3d_algo.execute()

print( "output_image:", str( dilation_3d_algo.output_image ) )

ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" );

Dilation3d dilation3dAlgo = new Dilation3d
{
    inputImage = foam,
    kernelRadius = 3,
    neighborhood = Dilation3d.Neighborhood.CONNECTIVITY_26
};
dilation3dAlgo.Execute();

Console.WriteLine( "outputImage:" + dilation3dAlgo.outputImage.ToString() );

Function Examples

auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" );

auto result = dilation3d( foam, 3, Dilation3d::Neighborhood::CONNECTIVITY_26 );

std::cout << "outputImage:" << result->toString();

foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip"))

result = imagedev.dilation_3d( foam, 3, imagedev.Dilation3d.CONNECTIVITY_26 )

print( "output_image:", str( result ) )

ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" );

IOLink.ImageView result = Processing.Dilation3d( foam, 3, Dilation3d.Neighborhood.CONNECTIVITY_26 );

Console.WriteLine( "outputImage:" + result.ToString() );