DirectionEdgeStatisticalCommand Class

Summary

Detects the variation of colors in the specified direction using statistical indices. It is similar to EdgeDetectStatisticalCommand, but this command allows you to specify the direction angle.

Syntax

Objective-C

C++/CLI

Java

Python

public class DirectionEdgeStatisticalCommand : RasterCommand

@interface LTDirectionEdgeStatisticalCommand : LTRasterCommand

public class DirectionEdgeStatisticalCommand 
    extends RasterCommand

public ref class DirectionEdgeStatisticalCommand : public RasterCommand

class DirectionEdgeStatisticalCommand(RasterCommand):

Remarks

The edges are detected by applying a statistical filter that analyzes the variations of colors in a specified direction around each pixel.
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.

For more information, refer to Detecting and Enhancing Edges and Lines.

Direction Edge Statistical Function - Before

Direction Edge Statistical Function - After

View additional platform support for this Direction Edge Statistical function.

Example

Run the DirectionEdgeStatisticalCommand on an image, to find it is edges.

Java

using Leadtools; 
using Leadtools.Codecs; 
using Leadtools.ImageProcessing.Effects; 
 
 
public void DirectionEdgeStatisticalCommandExample() 
{ 
   // 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 
   DirectionEdgeStatisticalCommand command = new DirectionEdgeStatisticalCommand(); 
 
   command.Dimension = 15; 
   command.Threshold = 128; 
   command.Angle = 4500; 
   command.EdgeColor = new RasterColor(255, 255, 255); 
   command.BackGroundColor = new RasterColor(0, 0, 0); 
 
   //Find the edges in the image. 
   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.*; 
 
import leadtools.*; 
import leadtools.codecs.*; 
import leadtools.imageprocessing.effects.DirectionEdgeStatisticalCommand; 
 
 
public void directionEdgeStatisticalCommandExample() { 
    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 
    DirectionEdgeStatisticalCommand command = new DirectionEdgeStatisticalCommand(); 
 
    command.setDimension(15); 
    command.setThreshold(128); 
    command.setAngle(4500); 
    command.setEdgeColor(new RasterColor(255, 255, 255)); 
    command.setBackGroundColor(new RasterColor(0, 0, 0)); 
 
    // Find the edges in the image 
    int change = command.run(image); 
    assertTrue(change != RasterImageChangedFlags.NONE); 
 
    codecs.save(image, combine(LEAD_VARS_IMAGES_DIR, "Result.jpg"), RasterImageFormat.JPEG, 24); 
    System.out.println("Command run and image saved to " + combine(LEAD_VARS_IMAGES_DIR, "Result.jpg")); 
}