/// <summary>
/// Draw the keypoints found on the image.
/// </summary>
/// <param name="image">The image</param>
/// <param name="keypoints">The keypoints to be drawn</param>
/// <param name="color">The color used to draw the keypoints</param>
/// <param name="type">The drawing type</param>
/// <param name="outImage">The image with the keypoints drawn</param>
public static void DrawKeypoints(
IInputArray image,
VectorOfKeyPoint keypoints,
IInputOutputArray outImage,
Bgr color,
Features2DToolbox.KeypointDrawType type)
{
MCvScalar c = color.MCvScalar;
using (InputArray iaImage = image.GetInputArray())
using (InputOutputArray ioaOutImage = outImage.GetInputOutputArray())
CvInvoke.drawKeypoints(iaImage, keypoints, ioaOutImage, ref c, type);
}
/// <summary>
/// Detect the if the model features exist in the observed features. If true, an homography matrix is returned, otherwise, null is returned.
/// </summary>
/// <param name="modelDescriptors">The descriptors from the model image</param>
/// <param name="modelKeyPoints">The keypoints drom the model image</param>
/// <param name="observedDescriptors">The descriptors from the descriptor image</param>
/// <param name="observedKeyPoints">The keypoints from the observed image</param>
/// <param name="uniquenessThreshold">The distance different ratio which a match is consider unique, a good number will be 0.8</param>
/// <returns>If the model features exist in the observed features, an homography matrix is returned, otherwise, null is returned.</returns>
public static HomographyMatrix Detect(
VectorOfKeyPoint modelKeyPoints, Matrix <TDescriptor> modelDescriptors,
VectorOfKeyPoint observedKeyPoints, Matrix <TDescriptor> observedDescriptors, double uniquenessThreshold)
{
int k = 2;
DistanceType dt = typeof(TDescriptor) == typeof(Byte) ? DistanceType.Hamming : DistanceType.L2;
using (Matrix <int> indices = new Matrix <int>(observedKeyPoints.Size, k))
using (Matrix <float> dist = new Matrix <float>(indices.Size))
using (BruteForceMatcher <TDescriptor> matcher = new BruteForceMatcher <TDescriptor>(dt))
using (Matrix <byte> mask = new Matrix <byte>(dist.Rows, 1))
{
matcher.Add(modelDescriptors);
matcher.KnnMatch(observedDescriptors, indices, dist, k, null);
mask.SetValue(255);
//Stopwatch w1 = Stopwatch.StartNew();
Features2DToolbox.VoteForUniqueness(dist, uniquenessThreshold, mask);
//Trace.WriteLine(w1.ElapsedMilliseconds);
int nonZeroCount = CvInvoke.cvCountNonZero(mask);
if (nonZeroCount < 4)
{
return(null);
}
//Stopwatch w2 = Stopwatch.StartNew();
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(modelKeyPoints, observedKeyPoints, indices, mask, 1.5, 20);
if (nonZeroCount < 4)
{
return(null);
}
return(Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(modelKeyPoints, observedKeyPoints, indices, mask, 3));
}
}
