public static void FindMatches(Mat modelImage, Mat observedImage, out VectorOfKeyPoint modelKeyPoints, out VectorOfKeyPoint observedKeyPoints, VectorOfVectorOfDMatch matches, out Mat mask, out Mat homography, MatchingTechnique matchingTechnique, float keyPointFilter = 1, double detectorParameter = -1)
{
int k = 2;
double uniquenessThreshold = 0.8;
homography = null;
modelKeyPoints = new VectorOfKeyPoint();
observedKeyPoints = new VectorOfKeyPoint();
Feature2D detector;
Feature2D descriptor;
DistanceType distanceType;
if (matchingTechnique == MatchingTechnique.FAST)
{
if (detectorParameter <= 0)
{
detectorParameter = 20;
}
detector = new FastDetector((int)detectorParameter);
descriptor = new BriefDescriptorExtractor();
distanceType = DistanceType.Hamming;
}
else if (matchingTechnique == MatchingTechnique.ORB)
{
if (detectorParameter <= 0)
{
detectorParameter = 100000;
}
detector = new ORBDetector((int)detectorParameter);
descriptor = detector;
distanceType = DistanceType.Hamming;
}
else if (matchingTechnique == MatchingTechnique.SURF)
{
if (detectorParameter <= 0)
{
detectorParameter = 300;
}
detector = new SURF(detectorParameter);
descriptor = detector;
distanceType = DistanceType.L2;
}
else
{
throw new NotImplementedException($"{matchingTechnique} not supported.");
}
// Extract features from model image.
UMat modelDescriptors = new UMat();
detector.DetectRaw(modelImage, modelKeyPoints, null);
Console.WriteLine($"modelKeyPoints: {modelKeyPoints.Size}");
if (keyPointFilter < 2)
{
modelKeyPoints = GetBestKeypointsPercent(modelKeyPoints, keyPointFilter);
}
else
{
modelKeyPoints = GetBestKeypointsCount(modelKeyPoints, (int)keyPointFilter);
}
descriptor.Compute(modelImage, modelKeyPoints, modelDescriptors);
// Extract features from observed image.
UMat observedDescriptors = new UMat();
detector.DetectRaw(observedImage, observedKeyPoints, null);
Console.WriteLine($"observedKeyPoints: {observedKeyPoints.Size}");
if (keyPointFilter < 2)
{
observedKeyPoints = GetBestKeypointsPercent(observedKeyPoints, keyPointFilter);
}
else
{
observedKeyPoints = GetBestKeypointsCount(observedKeyPoints, (int)keyPointFilter);
}
descriptor.Compute(observedImage, observedKeyPoints, observedDescriptors);
// Match keypoints.
BFMatcher matcher = new BFMatcher(distanceType);
matcher.Add(modelDescriptors);
matcher.KnnMatch(observedDescriptors, matches, k, null);
mask = new Mat(matches.Size, 1, DepthType.Cv8U, 1);
mask.SetTo(new MCvScalar(255));
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= 4)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, matches, mask, 1.5, 20);
if (nonZeroCount >= 4)
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, matches, mask, 2);
}
}
}
/// <summary>
/// Draw the model image and observed image, the matched features and homography projection.
/// </summary>
/// <param name="modelImage">The model image</param>
/// <param name="observedImage">The observed image</param>
/// <returns>The model image and observed image, the matched features and homography projection.</returns>
public Bitmap GetImageWithDrawnMatches(Bitmap modelImage, Bitmap observedImage, MatchingTechnique matchingTechnique)
{
VectorOfKeyPoint modelKeyPoints;
VectorOfKeyPoint observedKeyPoints;
using (Image <Bgr, byte> modelImg = new Image <Bgr, byte>(modelImage))
using (Image <Bgr, byte> observedImg = new Image <Bgr, byte>(observedImage))
using (Emgu.CV.Mat modelMat = modelImg.Mat)
using (Emgu.CV.Mat observedMat = observedImg.Mat)
using (VectorOfVectorOfDMatch matches = new VectorOfVectorOfDMatch())
{
ImageFeatureDetector.FindMatches(modelMat, observedMat, out modelKeyPoints, out observedKeyPoints, matches, out Mat mask, out Mat homography, matchingTechnique);
try
{
using (Mat result = new Mat())
{
Features2DToolbox.DrawMatches(modelMat, modelKeyPoints, observedMat, observedKeyPoints, matches, result, new MCvScalar(255, 0, 0), new MCvScalar(0, 0, 255), mask);
return(result.ToBitmap());
}
}
catch (Exception)
{
throw;
}
finally
{
mask?.Dispose();
homography?.Dispose();
}
}
}
