EdgeDetectStatisticalCommand Constructor(int,int,RasterColor,RasterColor)

Summary

Initializes a new EdgeDetectStatisticalCommand class object with explicit parameters.

Syntax

Objective-C

C++/CLI

Java

Python

public EdgeDetectStatisticalCommand( 
   int dimension, 
   int threshold, 
   RasterColor edgeColor, 
   RasterColor backGroundColor 
)

- (instancetype)initWithDimension:(NSUInteger)dimension threshold:(NSInteger)threshold edgeColor:(LTRasterColor*)edgeColor backgroundColor:(LTRasterColor *)backgroundColor NS_DESIGNATED_INITIALIZER;

public EdgeDetectStatisticalCommand( 
   int dimension, 
   int threshold, 
   RasterColor edgeColor, 
   RasterColor backGroundColor 
);

public: 
EdgeDetectStatisticalCommand(  
   int dimension, 
   int threshold, 
   RasterColor edgeColor, 
   RasterColor backGroundColor 
)

__init__(self,dimension,threshold,edgeColor,backGroundColor) # Overloaded constructor

Parameters

dimension
Dimensions of the neighborhood used to detect edges (Dimension x Dimension), in pixels. This parameter only accepts positive values.

threshold
Threshold value used to determine which pixels are edge pixels. If the difference determined by the edge detector algorithm for a pixel is greater than this value, the pixel is an edge pixel. This parameter only accepts positive values.

edgeColor
Edge color.

backGroundColor
Non edge color.

Example

Run the EdgeDetectStatisticalCommand on an image.

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Effects; 
 
 
public void EdgeDetectStatisticalConstructorExample() 
{ 
   // 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 
   EdgeDetectStatisticalCommand command = new EdgeDetectStatisticalCommand(5, 100, new RasterColor(255, 255, 255), new RasterColor(0, 0, 0)); 
   // Apply an edge detector statistical command. 
   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 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.effects.EdgeDetectStatisticalCommand; 
 
 
public void edgeDetectStatisticalConstructorExample() { 
   final String LEAD_VARS_IMAGES_DIR = "C:\\LEADTOOLS23\\Resources\\Images"; 
 
   // Load an image 
   RasterCodecs codecs = new RasterCodecs(); 
   codecs.setThrowExceptionsOnInvalidImages(true); 
 
   RasterImage image = codecs.load(combine(LEAD_VARS_IMAGES_DIR, "NaturalFruits.jpg")); 
 
   // Prepare the command 
   EdgeDetectStatisticalCommand command = new EdgeDetectStatisticalCommand(5, 100, new RasterColor(255, 255, 255), 
         new RasterColor(0, 0, 0)); 
 
   // Apply an edge detector statistical command. 
   int change = command.run(image); 
   assertTrue(change != RasterImageChangedFlags.NONE); 
 
   codecs.save(image, combine(LEAD_VARS_IMAGES_DIR, "naturalFruitsConstructorResult.jpg"), RasterImageFormat.JPEG, 
         24); 
   System.out.println( 
         "Command run, image saved to " + combine(LEAD_VARS_IMAGES_DIR, "naturalFruitsConstructorResult.jpg")); 
}

Requirements

Target Platforms

Reference

EdgeDetectStatisticalCommand Class

EdgeDetectStatisticalCommand Members

Overload List

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Help Version 23.0.2024.3.3

Leadtools.ImageProcessing.Effects Assembly

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