/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
///
public object Clone()
{
var clone = new HarrisCornersDetector();
clone.initialize(measure, k, threshold, sigma, r, size);
return(clone);
}
private void button1_Click(object sender, EventArgs e)
{
// Open a image
Bitmap lenna = Properties.Resources.lena512;
double sigma = (double)numSigma.Value;
float k = (float)numK.Value;
float threshold = (float)numThreshold.Value;
// Create a new Harris Corners Detector using the given parameters
HarrisCornersDetector harris = new HarrisCornersDetector(k)
{
Measure = checkBox1.Checked ?
HarrisCornerMeasure.Harris : HarrisCornerMeasure.Noble,
Threshold = threshold,
Sigma = sigma
};
// Create a new AForge's Corner Marker Filter
CornersMarker corners = new CornersMarker(harris, Color.White);
// Apply the filter and display it on a picturebox
pictureBox1.Image = corners.Apply(lenna);
}
public void ProcessImageTest()
{
UnmanagedImage image = UnmanagedImage.FromManagedImage(Accord.Imaging.Image.Clone(Properties.Resources.image1));
HarrisCornersDetector target = new HarrisCornersDetector(0.04f, 1000f, 1.4);
target.Suppression = 1;
List<IntPoint> actual = target.ProcessImage(image);
/*
PointsMarker marker = new PointsMarker(actual.ToArray());
marker.Width = 1;
marker.MarkerColor = Color.FromArgb(128, 128, 128);
var markers = marker.Apply(image);
ImageBox.Show(markers.ToManagedImage(), PictureBoxSizeMode.Zoom);
*/
/*
Assert.AreEqual(4, actual.Count);
Assert.IsTrue(actual.Contains(new IntPoint(3, 3)));
Assert.IsTrue(actual.Contains(new IntPoint(14, 3)));
Assert.IsTrue(actual.Contains(new IntPoint(3, 14)));
Assert.IsTrue(actual.Contains(new IntPoint(14, 14)));
*/
Assert.AreEqual(4, actual.Count);
Assert.IsTrue(actual.Contains(new IntPoint(3, 3)));
Assert.IsTrue(actual.Contains(new IntPoint(12, 3)));
Assert.IsTrue(actual.Contains(new IntPoint(3, 12)));
Assert.IsTrue(actual.Contains(new IntPoint(12, 12)));
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
protected override object Clone(ISet <PixelFormat> supportedFormats)
{
var clone = new HarrisCornersDetector();
clone.SupportedFormats = supportedFormats;
clone.initialize(measure, k, threshold, sigma, r, size);
return(clone);
}
public List <Rg.Point3d> GetHarrisCorners()
{
Ai.HarrisCornersDetector corners = new Ai.HarrisCornersDetector();
if (Threshold >= 0)
{
corners.Threshold = Threshold;
}
if (Value >= 0)
{
corners.Sigma = Value;
}
return(corners.ProcessImage(bitmap).ToRhinoPoints(bitmap.Height));
}
private void BtnHarris_OnClick(object sender, RoutedEventArgs e)
{
// Step 1: Detect feature points using Harris Corners Detector
HarrisCornersDetector harris = new HarrisCornersDetector(0.04f, 1000f);
harrisPoints1 = harris.ProcessImage(img1).ToArray();
harrisPoints2 = harris.ProcessImage(img2).ToArray();
// Show the marked points in the original images
Bitmap img1mark = new PointsMarker(harrisPoints1).Apply(img1);
Bitmap img2mark = new PointsMarker(harrisPoints2).Apply(img2);
// Concatenate the two images together in a single image (just to show on screen)
Concatenate concatenate = new Concatenate(img1mark);
PictureBox.Source = concatenate.Apply(img2mark);
}
public void ProcessImageTest2()
{
UnmanagedImage image = UnmanagedImage.FromManagedImage(Accord.Imaging.Image.Clone(Properties.Resources.sample_black));
HarrisCornersDetector target = new HarrisCornersDetector(HarrisCornerMeasure.Noble, 700f, 1.4, 1);
List<IntPoint> actual = target.ProcessImage(image);
/*
PointsMarker marker = new PointsMarker(actual.ToArray());
marker.Width = 3;
marker.MarkerColor = Color.FromArgb(255, 0, 0);
var markers = marker.Apply(image);
ImageBox.Show(markers.ToManagedImage(), PictureBoxSizeMode.Zoom);
*/
Assert.AreEqual(actual.Count, 42);
}
/// <summary>
/// Detect keypoints in images using Harris corner detector from Accord.NET library
/// http://accord-framework.net/docs/html/T_Accord_Imaging_HarrisCornersDetector.htm
/// </summary>
private void detectKeypoints_Harris()
{
HarrisCornersDetector harris_detector = new HarrisCornersDetector(0.04f, 500f);
for (int i = 0; i < input_images.Count; i++)
{
if (i != 0) //if not first image, calculate left side keypoints
{
keypoints.Add(harris_detector.ProcessImage(GetCroppedImage(input_images[i], ImageSection.Left)));
}
if (i != input_images.Count - 1) //if not last image, calculate right side keypoints
{
keypoints.Add(harris_detector.ProcessImage(GetCroppedImage(input_images[i], ImageSection.Right)));
}
}
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
///
public object Clone()
{
var clone = new HarrisCornersDetector();
clone.initialize(measure, k, threshold, sigma, r, size);
return clone;
}
private bool GenerateKeypointMatches(Bitmap target, Bitmap frame, Rectangle prevTarget)
{
HarrisCornersDetector harrisDetector = new HarrisCornersDetector(HarrisCornerMeasure.Harris, 1000f, 1f, 2);
targetKeyPoints=harrisDetector.ProcessImage(target).ToArray();
frameKeyPoints=harrisDetector.ProcessImage(frame).ToArray();
//Console.WriteLine("tr={0} fr={1}", targetKeyPoints.Length, frameKeyPoints.Length);
if (targetKeyPoints.Length==0||frameKeyPoints.Length==0)
{
return false;
}
CorrelationMatching matcher=new CorrelationMatching(15);
IntPoint[][] matches=matcher.Match(target, frame, targetKeyPoints, frameKeyPoints);
targetMacthes=matches[0];
frameMatches=matches[1];
if (targetMacthes.Length<4||frameMatches.Length<4)
{
return false;
}
RansacHomographyEstimator ransac=new RansacHomographyEstimator(0.1, 0.50);
MatrixH estiment = new MatrixH();
try
{
estiment = ransac.Estimate(targetMacthes, frameMatches);
}
catch
{
return false;
}
IntPoint[] targetGoodMatch=targetMacthes.Submatrix(ransac.Inliers);
IntPoint[] frameGoodMatch=frameMatches.Submatrix(ransac.Inliers);
CalculatePosChange(targetGoodMatch, frameGoodMatch, prevTarget);
return true;
}
private void harris_Click(object sender, EventArgs e)
{
// Open a image
Bitmap image = new Bitmap(sourcePic.Image);
double sigma = 1.4;
float k = 0.04f;
float threshold = 20000;
// Create a new Harris Corners Detector using the given parameters
HarrisCornersDetector harris = new HarrisCornersDetector(k)
{
Threshold = threshold,
Sigma = sigma
};
// Create a new AForge's Corner Marker Filter
CornersMarker corners = new CornersMarker(harris, Color.White);
// Apply the filter and display it on a picturebox
processedPic.Image = corners.Apply(image);
}
private void UpdateDetector()
{
harris = new HarrisCornersDetector(configuration.K)
{
Threshold = configuration.Threshold,
Sigma = configuration.Sigma
};
matcher = new KNearestNeighborMatching(configuration.NoNearestNeighborMatching);
}
// PANORAMIC STICHING CODE
// Accord.NET and AForge.NET frameworks and code examples provided from
// http://www.codeproject.com/KB/recipes/automatic_panoramas.aspx
private void panoramicStitchingToolStripMenuItem_Click(object sender, EventArgs e)
{
// Save a copy of the current image, ask user to open another image to merge with
Bitmap img2 = img;
openToolStripMenuItem_Click(sender, e);
// Check whether the current loaded image is different
// (If the user cancelled the open image operation, the current image in the viewer
// is still the same image object)
if (img2 != img)
{
Bitmap img1 = img;
AForge.IntPoint[] harrisPoints1;
AForge.IntPoint[] harrisPoints2;
AForge.IntPoint[] correlationPoints1;
AForge.IntPoint[] correlationPoints2;
MatrixH homography;
// Use Harris Corners Detector to find points of interest
HarrisCornersDetector harris = new HarrisCornersDetector(0.04f, 1000f);
harrisPoints1 = harris.ProcessImage(img1).ToArray();
harrisPoints2 = harris.ProcessImage(img2).ToArray();
// This check fixes an out of bounds exception generated by matcher.Match() below when a
// monocolour image (0 harris points) is stitched with a non-monocolour image
if (harrisPoints1.Length == 0 || harrisPoints2.Length == 0)
{
MessageBox.Show("Panoramic stitching cannot continue because at least one of the images does not contain any Harris points.", "Warning");
}
else
{
// Match detected points using correlation
CorrelationMatching matcher = new CorrelationMatching(9);
AForge.IntPoint[][] matches = matcher.Match(img1, img2, harrisPoints1, harrisPoints2);
// Separate the two arrays
correlationPoints1 = matches[0];
correlationPoints2 = matches[1];
// Find homography matrix using RANSAC algorithm
RansacHomographyEstimator ransac = new RansacHomographyEstimator(0.001, 0.99);
// This check is to handle the ransac.Estimate() function
// which throws an exception if the array parameters do not contain at least 4 elements
if (correlationPoints1.Length < 4 || correlationPoints2.Length < 4)
{
MessageBox.Show("Panoramic stitching cannot continue because at least one of the images does not contain at least 4 correlation points.", "Warning");
}
else
{
homography = ransac.Estimate(correlationPoints1, correlationPoints2);
// Merge the images
Blend blend = new Blend(homography, img1);
img = blend.Apply(img2);
//save the image properly and resize main form
origImg.Dispose();
origImg = new Bitmap(img);
pictureBox.Image = img;
mainForm.ActiveForm.Width = img.Width + widthPad;
mainForm.ActiveForm.Height = img.Height + heightPad;
}
}
}
}