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MinimumCommand Class

Summary
Dilates dark objects by the specified amount. This command is available in the Document/Medical toolkits.
Syntax
C#
Objective-C
C++/CLI
Java
Python
public class MinimumCommand : RasterCommand 
@interface LTMinimumCommand : LTRasterCommand 
public class MinimumCommand 
    extends RasterCommand 
public ref class MinimumCommand : public RasterCommand   
class MinimumCommand(RasterCommand): 
Remarks
  • This command can process the whole image or a region of the image.
  • The effect can be controlled by specifying the size of the neighborhood that is used for calculating each pixel value. For example, for 8x8, set the Dimension property to 8 or pass 8 for the dimension parameter of the Constructor. Each pixel is replaced with the minimum value of its neighborhood.
  • This command 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 signed/unsigned data images.

For more information, refer to Removing Noise.

Minimum Function - Before

Minimum Function - Before

Minimum Function - After

Minimum Function - After

View additional platform support for this Minimum function.

Example

Run the MinimumCommand on an image with a neighborhood Dimensions = 3x3 pixels.

C#
Java
using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Core; 
 
public void MinimumCommandExample() 
{ 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.ThrowExceptionsOnInvalidImages = true; 
 
   RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, @"ImageProcessingDemo\NaturalFruits.jpg")); 
 
   // Prepare the command 
   MinimumCommand command = new MinimumCommand(); 
   //Apply the Minimum filter. 
   command.Dimension = 3; 
   command.Run(image); 
 
} 
 
static class LEAD_VARS 
{ 
   public const string ImagesDir = @"C:\LEADTOOLS23\Resources\Images"; 
} 
 
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 static org.junit.Assert.assertTrue; 
 
import leadtools.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.core.MinimumCommand; 
 
 
public void minimumCommandExample() { 
   final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
   final String outputFileName = 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, "NaturalFruits.jpg")); 
 
   // Prepare the command 
   MinimumCommand command = new MinimumCommand(); 
 
   // Apply the Minimum filter. 
   command.setDimension(3); 
   command.run(image); 
   codecs.save(image, outputFileName, RasterImageFormat.JPEG, 0); 
 
   assertTrue(new File(outputFileName).exists()); 
   System.out.println("Command run and image saved to " + outputFileName); 
} 
Requirements

Target Platforms

Help Version 23.0.2024.3.3
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© 1991-2024 LEAD Technologies, Inc. All Rights Reserved.

Leadtools.ImageProcessing.Core Assembly
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© 1991-2023 LEAD Technologies, Inc. All Rights Reserved.