ImageDev

InfluenceZones

Computes the Skeleton by Influence Zone (SKIZ).

Access to parameter description

For an introduction: This algorithm produces a pruned skeleton of the background.
The influence zone of a particle $X_i$ is the set of points closer to $X_i$ than to any other particle $X_j$.
The skeleton by influence zones is the boundary splitting the different influence zones, and it separates the image into zones surrounding each object.

<b> Figure 1.</b> Skeleton by influence zones (SKIZ)
Figure 1. Skeleton by influence zones (SKIZ)

This algorithm searches the skeleton of a binary or labeled image by influence zones.
If the input is a binary image, it is first labelled, then the influence zones are determined by successive conditional dilations. $$ \begin{array}{ccc} 2 & 2 & 2\\ 1 & \bullet & 2\\ 1 & 1 & 1 \end{array} $$
The process stops as soon as all the zones are hitting each other.

See also

Function Syntax

This function returns outputBinaryImage. 
// Function prototype
std::shared_ptr< iolink::ImageView >
influenceZones( std::shared_ptr< iolink::ImageView > inputObjectImage,
                InfluenceZones::Neighborhood neighborhood,
                std::shared_ptr< iolink::ImageView > outputBinaryImage = nullptr );
This function returns outputBinaryImage. 
// Function prototype.
influence_zones(input_object_image: idt.ImageType,
                neighborhood: InfluenceZones.Neighborhood = InfluenceZones.Neighborhood.CONNECTIVITY_26,
                output_binary_image: idt.ImageType = None) -> idt.ImageType
This function returns outputBinaryImage. 
// Function prototype.
public static IOLink.ImageView
InfluenceZones( IOLink.ImageView inputObjectImage,
                InfluenceZones.Neighborhood neighborhood = ImageDev.InfluenceZones.Neighborhood.CONNECTIVITY_26,
                IOLink.ImageView outputBinaryImage = null );

Class Syntax

Parameters

Parameter Name Description Type Supported Values Default Value
input
inputObjectImage
The binary input or label image. Image Binary or Label nullptr
input
neighborhood
The 3D neighborhood configuration. This parameter is ignored with a 2D input image.
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
outputBinaryImage
The binary output image. Its size and type are forced to the same values as the input. Image nullptr
Parameter Name Description Type Supported Values Default Value
input
input_object_image
The binary input or label image. image Binary or Label None
input
neighborhood
The 3D neighborhood configuration. This parameter is ignored with a 2D input image.
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_binary_image
The binary output image. Its size and type are forced to the same values as the input. image None
Parameter Name Description Type Supported Values Default Value
input
inputObjectImage
The binary input or label image. Image Binary or Label null
input
neighborhood
The 3D neighborhood configuration. This parameter is ignored with a 2D input image.
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
outputBinaryImage
The binary output image. Its size and type are forced to the same values as the input. Image null

Object Examples

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

InfluenceZones influenceZonesAlgo;
influenceZonesAlgo.setInputObjectImage( foam_sep );
influenceZonesAlgo.setNeighborhood( InfluenceZones::Neighborhood::CONNECTIVITY_26 );
influenceZonesAlgo.execute();

std::cout << "outputBinaryImage:" << influenceZonesAlgo.outputBinaryImage()->toString();

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

influence_zones_algo = imagedev.InfluenceZones()
influence_zones_algo.input_object_image = foam_sep
influence_zones_algo.neighborhood = imagedev.InfluenceZones.CONNECTIVITY_26
influence_zones_algo.execute()

print("output_binary_image:", str(influence_zones_algo.output_binary_image))

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

InfluenceZones influenceZonesAlgo = new InfluenceZones
{
    inputObjectImage = foam_sep,
    neighborhood = InfluenceZones.Neighborhood.CONNECTIVITY_26
};
influenceZonesAlgo.Execute();

Console.WriteLine( "outputBinaryImage:" + influenceZonesAlgo.outputBinaryImage.ToString() );

Function Examples

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

auto result = influenceZones( foam_sep, InfluenceZones::Neighborhood::CONNECTIVITY_26 );

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

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

result = imagedev.influence_zones(foam_sep, imagedev.InfluenceZones.CONNECTIVITY_26)

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

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

IOLink.ImageView result = Processing.InfluenceZones( foam_sep, InfluenceZones.Neighborhood.CONNECTIVITY_26 );

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