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public FindStereoCorrespondence ( Byte>.Image |
||
| left | Byte>.Image | The left single-channel, 8-bit image |
| right | Byte>.Image | The right image of the same size and the same type |
| disparity | Int16>.Image | The output single-channel 16-bit signed disparity map of the same size as input images. Its elements will be the computed disparities, multiplied by 16 and rounded to integer's |
| Результат | void | |
public void TestStereoBMCorrespondence()
{
Image<Gray, Byte> left = new Image<Gray, byte>("left.jpg");
Image<Gray, Byte> right = new Image<Gray, byte>("right.jpg");
Image<Gray, Int16> leftDisparity = new Image<Gray, Int16>(left.Size);
Image<Gray, Int16> rightDisparity = new Image<Gray, Int16>(left.Size);
StereoBM bm = new StereoBM(Emgu.CV.CvEnum.STEREO_BM_TYPE.BASIC, 0);
Stopwatch watch = Stopwatch.StartNew();
bm.FindStereoCorrespondence(left, right, leftDisparity);
watch.Stop();
Trace.WriteLine(String.Format("Time used: {0} milliseconds", watch.ElapsedMilliseconds));
Matrix<double> q = new Matrix<double>(4, 4);
q.SetIdentity();
MCvPoint3D32f[] points = PointCollection.ReprojectImageTo3D(leftDisparity * (-16), q);
float min = (float)1.0e10, max = 0;
foreach (MCvPoint3D32f p in points)
{
if (p.z < min) min = p.z;
else if (p.z > max) max = p.z;
}
Trace.WriteLine(String.Format("Min : {0}\r\nMax : {1}", min, max));
}
private void ProcessImage(Bitmap image)
{
// Call the function to apply filtering and enhancement to the captured frame before processing for blobs
Bitmap CombinedImage = FilterImage(image);
// Create the processed L and R images for blob processing
Bitmap ProcessedL = filterL.Apply(CombinedImage);
Bitmap ProcessedR = filterR.Apply(CombinedImage);
// Free the memory from the filtered combined image
CombinedImage.Dispose();
// Create final L and R images based on source
Bitmap imageL = filterL.Apply(image);
Bitmap imageR = filterR.Apply(image);
// Eventually when done testing/tinkering/and generally toying with different techniques we need to eliminate the L and R images and only keep the overlay.
// Process the disparity map
StereoBM bm = new StereoBM(Emgu.CV.CvEnum.STEREO_BM_TYPE.BASIC, 0);
disparity = new Image<Gray, float>(xMax / 2, yMax);
bm.FindStereoCorrespondence(new Image<Gray, Byte>(ProcessedL), new Image<Gray, Byte>(ProcessedR), disparity);
//CvInvoke.cvConvertScale(disparity, disparity, 16, 0);
//CvInvoke.cvNormalize(disparity, disparity, 0, 255, Emgu.CV.CvEnum.NORM_TYPE.CV_MINMAX,IntPtr.Zero);
pictureBoxD.Image = disparity.ToBitmap(320, 240);
// Process the left
pictureBoxL.Image = ProcessBlobs(imageL, ProcessedL, Input.Left);
// Process the right
pictureBoxR.Image = ProcessBlobs(imageR, ProcessedR, Input.Right);
// Process the combined data
pictureBoxC.Image = ProcessFingerData();
disparity.Dispose(); // Free memory no longer needed
ProcessedL.Dispose(); // Free memory no longer needed
ProcessedR.Dispose(); // Free memory no longer needed
imageL.Dispose(); // Free memory no longer needed
imageR.Dispose(); // Free memory no longer needed
}
