IntensityDetectCommand Class

Summary

Applies binary segmentation to an image by filtering a specific image to detect colors in a specific intensity range, in a specific color channel(s).

Syntax

Objective-C

C++/CLI

Java

Python

public class IntensityDetectCommand : RasterCommand

@interface LTIntensityDetectCommand : LTRasterCommand

public class IntensityDetectCommand 
    extends RasterCommand

public ref class IntensityDetectCommand : public RasterCommand

class IntensityDetectCommand(RasterCommand):

Remarks

The image is divided into two parts, inner and outer according to the values of the LowThreshold property and the HighThreshold property.
The class can process 2 or more channels at a time by OR-ing two or more flags.
This class supports 12 and 16-bit grayscale and 48 and 64-bit color images. Support for 12 and 16-bit grayscale and 48 and 64-bit color images is available only in the Document/Medical toolkits.
This command does not support 32-bit grayscale images.
This command supports unsigned data images, but not signed ones.

For more information, refer to Changing Brightness and Contrast. For more information, refer to Correcting Colors. For more information, refer to Detecting and Enhancing Edges and Lines.

Intensity Detect Function - Before

Intensity Detect Function - After

View additional platform support for this Intensity Detect function.

Example

Run the IntensityDetectCommand on an image.

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Color; 
 
 
public void IntensityDetectCommandExample() 
{ 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "dirty_barcode.jpg")); 
 
   // Prepare the command 
   IntensityDetectCommand command = new IntensityDetectCommand(); 
   //Apply the filter. 
   command.LowThreshold = 128; 
   command.HighThreshold = 255; 
   command.InColor = new RasterColor(255, 255, 255); 
   command.OutColor = new RasterColor(0, 0, 0); 
   command.Channel = IntensityDetectCommandFlags.Master; 
   command.Run(image); 
   codecs.Save(image, Path.Combine(LEAD_VARS.ImagesDir, "Result.jpg"), RasterImageFormat.Jpeg, 24); 
 
} 
 
static class LEAD_VARS 
{ 
   public const string ImagesDir = @"C:\LEADTOOLS23\Resources\Images"; 
}

 
import static org.junit.Assert.assertTrue; 
 
import java.io.File; 
import java.io.IOException; 
 
import org.junit.*; 
import org.junit.runner.JUnitCore; 
import org.junit.runner.Result; 
import org.junit.runner.notification.Failure; 
 
import leadtools.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.color.IntensityDetectCommand; 
import leadtools.imageprocessing.color.IntensityDetectCommandFlags; 
 
 
public void intensityDetectCommandExample() { 
 
   final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
   final String outputFilePath = combine(LEAD_VARS_IMAGES_DIR, "Result.jpg"); 
 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.setThrowExceptionsOnInvalidImages(true); 
 
   RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "noisy_barcode.jpg")); 
 
   // Prepare the command 
   IntensityDetectCommand command = new IntensityDetectCommand(); 
   // Apply the filter. 
   command.setLowThreshold(128); 
   command.setHighThreshold(255); 
   command.setInColor(new RasterColor(255, 255, 255)); 
   command.setOutColor(new RasterColor(0, 0, 0)); 
   command.setChannel(IntensityDetectCommandFlags.MASTER.getValue()); 
   command.run(image); 
   codecs.save(image, outputFilePath, RasterImageFormat.JPEG, 24); 
 
   assertTrue(new File(outputFilePath).exists()); 
   System.out.println("Command run and image saved to " + outputFilePath); 
 
}