Label Analysis

This example shows how to extract individual measurements for each object of a segmented image.

First, a binary image is opened from a vip file. The vip file format is an internal format dedicated to store images with all relevant information for ImageDev. This image is immediately identified as a binary image and can be labeled with the Label2d algorithm.

Then, an AnalysisMsr object is initialized. It is set up to contain two measurements: EquivalentDiameter2d and FeretRatio2d. At last, the analysis is performed and both measurements are computed for each object of the label image. The results are printed in the standard output.

Performing the label analysis...
Number of objects = 58
Label	EquivalentDiameter	FeretRatio2d
1	57.83	1.04
2	49.03	1.00
3	50.49	1.02
4	60.69	1.02

#include <ImageDev/Data/NativeMeasurements.h>
#include <ImageDev/ImageDev.h>
#include <ioformat/IOFormat.h>

using namespace imagedev;
using namespace ioformat;
using namespace iolink;

int
main()
{
    // ImageDev library initialization
    if ( isInitialized() == false )
        imagedev::init();

    // Open a binary image from a vip file
    auto imageInput = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene_sep.vip" );

    // Connected component labeling of the binary image
    std::cout << "Labeling the binary input..." << std::endl;
    auto imageLab = labeling2d( imageInput, Labeling2d::LABEL_8_BIT, Labeling2d::CONNECTIVITY_8 );

    // Define the analysis features to be computed
    std::cout << "Performing the label analysis..." << std::endl;
    AnalysisMsr::Ptr analysis = std::make_shared< AnalysisMsr >();
    auto diameter = analysis->select( NativeMeasurements::equivalentDiameter );
    auto feretRatio = analysis->select( NativeMeasurements::feretRatio2d );

    // Launch the feature extraction on the segmented image
    labelAnalysis( imageLab, imageInput, analysis );
    size_t labelCount = analysis->labelCount();
    std::cout << "  - Number of objects = " << labelCount << std::endl;
    // Print the 4 first results of the analysis
    std::cout << "Label\t" << diameter->name() << "\t" << feretRatio->name() << std::endl;
    for ( int i = 0; i < 4; i++ )
    {
        std::cout << ( i + 1 ) << "\t" << diameter->value( i ) << "\t\t\t" << feretRatio->value( i ) << std::endl;
    }

    // ImageDev library finalization
    imagedev::finish();

    return 0;
}

using System;
using ImageDev;
using IOLink;
using IOFormat;

namespace T04_02_LabelAnalysis
{
    class Program
    {
        static void Main( string[] args )
        {
            // ImageDev library initialization
            if ( Initialization.IsInitialized() == false )
                Initialization.Init();

            // Open a binary image from a vip file
            ImageView imageInput = Data.ReadVipImage( @"Data/images/polystyrene_sep.vip" ) as ImageView;

            // Connected component labeling of a binary image
            Console.WriteLine( "Labeling the binary input..." );
            var imageLab = Processing.Labeling2d( imageInput );

            // Define the analysis features to be computed
            Console.WriteLine( "Performing the label analysis..." );
            AnalysisMsr analysis = new AnalysisMsr();
            var diameter = analysis.Select( NativeMeasurements.EquivalentDiameter );
            var feretRatio = analysis.Select( NativeMeasurements.FeretRatio2d );

            // Launch the feature extraction on the segmented image
            Processing.LabelAnalysis( imageLab, imageInput, analysis );
            int labelCount = analysis.LabelCount();
            Console.WriteLine( "  - Number of objects = " + labelCount );
            Console.WriteLine( "Label\t" + diameter.Name() + "\t" + feretRatio.Name() );
            // Print the 4 first results of the analysis
            for ( int i = 0; i < 4; i++ )
            {
                Console.WriteLine( ( i + 1 ) + "\t" + diameter.Value( i ).ToString( "0.00" ) + "\t\t\t" +
                                   feretRatio.Value( i ).ToString( "0.00" ) );
            }

            // Notify the garbage collector that the created images can be freed
            imageInput.Dispose();
            imageLab.Dispose();

            // ImageDev library finalization
            Initialization.Finish();
        }
    }
}

import imagedev
import imagedev_data

# Initialize the ImageDev library if not done
if (imagedev.is_initialized() == False): imagedev.init()

# Open a binary image from a vip file
image_input = imagedev.read_vip_image(imagedev_data.get_image_path("polystyrene_sep.vip"))

# Connected component labeling of the binary image
print("Labeling the binary input...")
image_lab = imagedev.labeling_2d(image_input, imagedev.Labeling2d.LabelType.LABEL_8_BIT)

# Define the analysis features to be computed
print("Performing the label analysis...")
analysis = imagedev.AnalysisMsr()
diameter = analysis.select(imagedev.native_measurements.EquivalentDiameter)
feret_ratio = analysis.select(imagedev.native_measurements.FeretRatio2d)

# Launch the feature extraction on the segmented image
imagedev.label_analysis(image_lab, image_input, analysis)
label_count = analysis.label_count
print("  - Number of objects = " + str(label_count))
# Print the 4 first results of the analysis
print("Label\t" + diameter.name + "\t" + feret_ratio.name)
for i in range(3):
  print(str(i+1) + '\t\t\t' + "{:.2f}".format(diameter.value(i)) + '\t\t\t\t' + "{:.2f}".format(feret_ratio.value(i)))

# ImageDev library finalization
imagedev.finish()

See also