public CorrelationCommand(
RasterImage correlationImage,
LeadPoint[] points,
int xStep,
int yStep,
int threshold
)
- (instancetype)initWithCorrelationImage:(nullable LTRasterImage *)correlationImage points:(nullable NSArray<NSValue *> *)points xStep:(NSUInteger)xStep yStep:(NSUInteger)yStep threshold:(NSUInteger)threshold NS_DESIGNATED_INITIALIZER;
public CorrelationCommand(
RasterImage correlationImage,
LeadPoint[] points,
int xStep,
int yStep,
int threshold
);
public:
CorrelationCommand(
RasterImage^ correlationImage,
array<LeadPoint>^ points,
int xStep,
int yStep,
int threshold
)
__init__(self,correlationImage,points,xStep,yStep,threshold) # Overloaded constructor
correlationImage
RasterImage object that references the image for which to search.
points
An array of LeadPoint structures. This array will be updated with the starting points for the correlated areas.
xStep
Step size in the X direction (along image width), in pixels. For best results, use 1. This parameter accepts only positive values.
yStep
Step size in the Y direction (along image height), in pixels. For best results, use 1. This parameter accepts only positive values.
threshold
Value that indicates the correlation threshold, which is a measure of association required to consider two areas to be correlated. If the correlation value between correlationImage and an area in the image to be searched (the Run method image) is less than the correlation threshold they are u ncorrelated. Valid values range from 0 (zero resemblance) to 100 (perfect resemblance).
Run the CorrelationCommand on an image.
using Leadtools;
using Leadtools.Codecs;
using Leadtools.ImageProcessing.Core;
public void CorrelationConstructorExample()
{
// Load an image
RasterCodecs codecs = new RasterCodecs();
codecs.ThrowExceptionsOnInvalidImages = true;
RasterImage image = codecs.Load(Path.Combine(LEAD_VARS.ImagesDir, "clean.tif"));
// Prepare the command
RasterImage dstImage = image.Clone();
LeadPoint[] points = new LeadPoint[90];
CorrelationCommand command = new CorrelationCommand(dstImage, points, 1, 1, 70);
// Apply the correlation filter.
command.Run(image);
MessageBox.Show("The number of points are:" + command.NumberOfPoints.ToString());
}
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.core.*;
public void correlationConstructorExample() {
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, "clean.tif"));
// Prepare the command
RasterImage dstImage = image.clone();
LeadPoint[] points = new LeadPoint[90];
CorrelationCommand command = new CorrelationCommand(dstImage, points, 1, 1, 70);
// Apply the correlation filter
command.run(image);
codecs.save(image, outputFilePath, RasterImageFormat.TIF, 0);
assertTrue(new File(outputFilePath).exists());
System.out.println("File saved to: " + outputFilePath);
}
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