public static PointF[] GetMatchBoundingBox(HomographyMatrix homography, SURFFeatureData template)
{
if (homography != null) //Get RoI box
{
//draw a rectangle along the projected model
PointF[] pts = new PointF[] {
new PointF(template.GetImg().ROI.Left, template.GetImg().ROI.Bottom),
new PointF(template.GetImg().ROI.Right, template.GetImg().ROI.Bottom),
new PointF(template.GetImg().ROI.Right, template.GetImg().ROI.Top),
new PointF(template.GetImg().ROI.Left, template.GetImg().ROI.Top)
};
homography.ProjectPoints(pts); //project points
return(pts);
}
else
{
return(null);
}
}
public static Image <Bgr, byte> MatchSURFFeatureByBF(SURFFeatureData template, SURFFeatureData observedScene, out long processingTime, out int pairCount)
{
//This matrix indicates which row is valid for the matches.
Matrix <byte> mask;
//Number of nearest neighbors to search for
int k = 5;
//The distance different ratio which a match is consider unique, a good number will be 0.8 , NNDR match
double uniquenessThreshold = 0.5; //default 0.8
//The resulting n*k matrix of descriptor index from the training descriptors
Matrix <int> trainIdx;
HomographyMatrix homography = null;
Stopwatch watch;
try
{
watch = Stopwatch.StartNew();
#region Surf for CPU
//match
BruteForceMatcher <float> matcher = new BruteForceMatcher <float>(DistanceType.L2Sqr);
matcher.Add(template.GetDescriptors());
trainIdx = new Matrix <int>(observedScene.GetDescriptors().Rows, k);
//The resulting n*k matrix of distance value from the training descriptors
using (Matrix <float> distance = new Matrix <float>(observedScene.GetDescriptors().Rows, k))
{
matcher.KnnMatch(observedScene.GetDescriptors(), trainIdx, distance, k, null);
mask = new Matrix <byte>(distance.Rows, 1);
mask.SetValue(255); //Mask is 拉式信號匹配
//http://stackoverflow.com/questions/21932861/how-does-features2dtoolbox-voteforuniqueness-work
//how the VoteForUniqueness work...
Features2DToolbox.VoteForUniqueness(distance, uniquenessThreshold, mask);
}
Image <Bgr, byte> result = null;
int nonZeroCount = CvInvoke.cvCountNonZero(mask); //means good match
Console.WriteLine("VoteForUniqueness nonZeroCount=> " + nonZeroCount.ToString());
if (nonZeroCount >= (template.GetKeyPoints().Size * 0.2)) //set 10
{
//50 is model and mathing image rotation similarity ex: m1 = 60 m2 = 50 => 60 - 50 <=50 so is similar
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(template.GetKeyPoints(), observedScene.GetKeyPoints(), trainIdx, mask, 1.2, 30); //default 1.5,10
Console.WriteLine("VoteForSizeAndOrientation nonZeroCount=> " + nonZeroCount.ToString());
if (nonZeroCount >= (template.GetKeyPoints().Size * 0.5)) //default 4 ,set 15
{
homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(template.GetKeyPoints(), observedScene.GetKeyPoints(), trainIdx, mask, 5);
}
PointF[] matchPts = GetMatchBoundingBox(homography, template);
//Draw the matched keypoints
result = Features2DToolbox.DrawMatches(template.GetImg(), template.GetKeyPoints(), observedScene.GetImg(), observedScene.GetKeyPoints(),
trainIdx, new Bgr(255, 255, 255), new Bgr(255, 255, 255), mask, Features2DToolbox.KeypointDrawType.NOT_DRAW_SINGLE_POINTS);
if (matchPts != null)
{
result.DrawPolyline(Array.ConvertAll <PointF, Point>(matchPts, Point.Round), true, new Bgr(Color.Red), 2);
}
}
#endregion
watch.Stop();
//Console.WriteLine("\nCal SURF Match time=======\n=> " + watch.ElapsedTicks.ToString() + "ms\nCal SURF Match time=======");
processingTime = watch.ElapsedMilliseconds;
pairCount = nonZeroCount;
return(result);
}
catch (CvException ex)
{
System.Windows.Forms.MessageBox.Show(ex.ErrorMessage);
processingTime = -1L;
pairCount = -1;
return(null);
}
}
