public mDifferenceEuclidean(Bitmap UnderlayBitmap, Bitmap OverlayBitmap, int ThresholdValue)
{
Threshold = ThresholdValue;
BitmapUnder = new mSetFormat(UnderlayBitmap, mFilter.BitmapTypes.Rgb24bpp).ModifiedBitmap;
BitmapOver = new mSetFormat(OverlayBitmap, mFilter.BitmapTypes.Rgb24bpp).ModifiedBitmap;
ModifiedBitmap = UnderlayBitmap;
Effect = new ThresholdedEuclideanDifference(Threshold);
Effect.OverlayImage = BitmapOver;
ModifiedBitmap = Effect.Apply(BitmapUnder);
}
/// <summary>
/// Called when videoPlayer receives a new frame.
/// </summary>
/// <param name="sender"></param>
/// <param name="image"></param>
private void videoPlayer_NewFrame(object sender, ref Bitmap frame)
{
if (previousFrame != null)
{
// find the thresholded euclidian difference between two subsequent frames
ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
threshold.OverlayImage = previousFrame;
var difference = threshold.Apply(frame);
// only keep big blobs
var filter = new BlobsFiltering();
filter.CoupledSizeFiltering = true;
filter.MinHeight = 50;
filter.MinWidth = 50;
filter.ApplyInPlace(difference);
// dilate remaining blobs
var dilate = new BinaryDilation3x3();
dilate.ApplyInPlace(difference);
dilate.ApplyInPlace(difference);
dilate.ApplyInPlace(difference);
dilate.ApplyInPlace(difference);
// put this image in the thresholded picturebox
thresholdedBox.Image = difference.Clone() as Bitmap;
// use this as a mask for the current frame
var mask = new ApplyMask(difference);
var maskedFrame = mask.Apply(frame);
// put this image in the masked picturebox
maskedBox.Image = maskedFrame.Clone() as Bitmap;
// now find all moving blobs
if (frameIndex % 10 == 0)
{
var counter = new BlobCounter();
counter.ProcessImage(difference);
// only keep blobs that:
// - do not overlap with known cars
// - do not overlap with other blobs
// - have crossed the middle of the frame
// - are at least 100 pixels tall
var blobs = counter.GetObjectsRectangles();
var newBlobs = from r in counter.GetObjectsRectangles()
where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r)) &&
!blobs.Any(b => b.IntersectsWith(r) && b != r) &&
r.Top >= 240 && r.Bottom <= 480 &&
r.Height >= 100
select r;
// set up new camshift trackers for each detected blob
foreach (var rect in newBlobs)
{
trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
}
}
// now kill all car trackers that have expanded by too much
trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// and kill all trackers that have lived for 30 frames
trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
// let all remaining trackers process the current frame
var img = UnmanagedImage.FromManagedImage(maskedFrame);
trackers
.ForEach(t => t.Tracker.ProcessFrame(img));
// remember this frame for next iteration
previousFrame.Dispose();
previousFrame = frame.Clone() as Bitmap;
// draw labels on all tracked cars
var outputFrame = frame.Clone() as Bitmap;
trackers
.FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
.ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// return the processed frame to the video
frame = outputFrame;
}
// or else just remember this frame for next iteration
else
{
previousFrame = frame.Clone() as Bitmap;
}
frameIndex++;
}
void FinalFrame_NewFrame(object sender, NewFrameEventArgs eventArgs)
{
video = (Bitmap)eventArgs.Frame.Clone();
video2 = (Bitmap)eventArgs.Frame.Clone();
//Color Tracking
if (trackchoice == 0)
{
if (radioButton1.Checked == true)
{
HSLFiltering filter = new HSLFiltering();
filter.Hue = new IntRange((int)HueMin, (int)HueMax);
filter.Saturation = new Range(SatMin, SatMax);
filter.Luminance = new Range(LumMin, LumMax);
filter.ApplyInPlace(video2);
objec(video2);
}
if (radioButton2.Checked == true)
{
// create filter
EuclideanColorFiltering filter = new EuclideanColorFiltering();
// set center colol and radius
filter.CenterColor = rgb;
filter.Radius = range;
// apply the filter
filter.ApplyInPlace(video2);
objec(video2);
}
}
// motion Tracking
if (trackchoice == 1)
{
currentImage = (Bitmap)eventArgs.Frame.Clone();
Bitmap tmpimage = Grayscale.CommonAlgorithms.BT709.Apply(currentImage), copyCurrentImage = currentImage;
if (backgroundImage != null)
{
ThresholdedEuclideanDifference thd = new ThresholdedEuclideanDifference(30);
thd.OverlayImage = backgroundImage;
tmpimage = thd.Apply(tmpimage);
}
BlobCounter blobcounter = new BlobCounter();
blobcounter.MinHeight = minheight;
blobcounter.MinWidth = minwidth;
blobcounter.FilterBlobs = true;
blobcounter.ObjectsOrder = ObjectsOrder.Area;
blobcounter.ProcessImage(tmpimage);
Rectangle[] rects = blobcounter.GetObjectsRectangles();
foreach (Rectangle rect in rects)
{
if (rects.Length >= 5)
{
Rectangle objectRect = rects[0];
g = Graphics.FromImage(currentImage);
using (Pen pen = new Pen(Color.Red, 6))
{
g.DrawRectangle(pen, objectRect);
}
g.Dispose();
}
}
backgroundImage = Grayscale.CommonAlgorithms.BT709.Apply(copyCurrentImage);
pictureBox1.Image = copyCurrentImage;
pictureBox2.Image = tmpimage;
}
if (trackchoice == 2)
{
if (radioButton1.Checked == true)
{
HSLFiltering filter = new HSLFiltering();
filter.Hue = new IntRange((int)HueMin, (int)HueMax);
filter.Saturation = new Range(SatMin, SatMax);
filter.Luminance = new Range(LumMin, LumMax);
filter.ApplyInPlace(video2);
//objec(video2);
}
if (radioButton2.Checked == true)
{
// create filter
EuclideanColorFiltering filter = new EuclideanColorFiltering();
// set center colol and radius
filter.CenterColor = rgb;
filter.Radius = range; //filter.Radius = 100;
// apply the filter
filter.ApplyInPlace(video2);
// objec(video2);
}
BlobCounter blobCounter = new BlobCounter();
blobCounter.MinWidth = minwidth;
blobCounter.MinHeight = minheight;
blobCounter.FilterBlobs = true;
blobCounter.ObjectsOrder = ObjectsOrder.Size;
blobCounter.ProcessImage(video2);
Rectangle[] recs = blobCounter.GetObjectsRectangles();
pictureBox2.Image = video2;
foreach (Rectangle rect in recs)
{
if (recs.Length >= 0)
{
Rectangle objectRect = recs[0];
x1 = objectRect.X;
y1 = objectRect.Y;
wdth = objectRect.Width;
hgth = objectRect.Height;
}
}
currentImage = (Bitmap)eventArgs.Frame.Clone();
Bitmap tmpimage = Grayscale.CommonAlgorithms.BT709.Apply(currentImage), copyCurrentImage = currentImage;
if (backgroundImage != null)
{
ThresholdedEuclideanDifference thd = new ThresholdedEuclideanDifference(50);
thd.OverlayImage = backgroundImage;
tmpimage = thd.Apply(tmpimage);
BlobCounter blobcounter = new BlobCounter();
blobcounter.MinHeight = minheight;
blobcounter.MinWidth = minwidth;
blobcounter.FilterBlobs = true;
blobcounter.ObjectsOrder = ObjectsOrder.Area;
blobcounter.ProcessImage(tmpimage);
Rectangle[] rects = blobcounter.GetObjectsRectangles();
foreach (Rectangle rect in rects)
{
if (rects.Length >= 5) //
{
Rectangle objectRect = rects[0];
x2 = objectRect.X;
y2 = objectRect.Y;
if ((x1 - 50 < x2) && (x2 < x1 + 50))
{
if ((y1 - 50 < y2) && (y2 < y1 + 50))
{
track = true;
counter = 25;
}
}
else
{
counter--;
}
if (counter == 0)
{
track = false;
}
if (track == true && counter > 0)
{
g = Graphics.FromImage(copyCurrentImage);
using (Pen pen = new Pen(Color.FromArgb(252, 3, 26), 6))
{
g.DrawRectangle(pen, x1, y1, wdth, hgth);
}
g.Dispose();
}
if (CheckCordinates.Checked)
{
this.Invoke((MethodInvoker) delegate
{
richTextBox1.Text = "X=[" + x1 + "], Y=[" + y1 + "]" + "\n" + richTextBox1.Text + "\n";;
});
}
}
}
}
backgroundImage = Grayscale.CommonAlgorithms.BT709.Apply(copyCurrentImage);
pictureBox1.Image = copyCurrentImage;
}
}
/// <summary>
/// Called when videoPlayer receives a new frame.
/// </summary>
/// <param name="sender"></param>
/// <param name="image"></param>
private void videoPlayer_NewFrame_1(object sender, ref Bitmap frame)
{
//if (cmb_fuente.SelectedIndex==1)
//{
// RotateBicubic filter = new RotateBicubic(90, true);
// frame = filter.Apply(frame);
//}
if (previousFrame != null)
{
// find the thresholded euclidian difference between two subsequent frames
//ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(thr);
threshold.OverlayImage = previousFrame;
var difference = threshold.Apply(frame);
// only keep big blobs
var filter = new BlobsFiltering();
filter.CoupledSizeFiltering = true;
filter.MinHeight = int.Parse(txt_tamanio2.Text);
filter.MinWidth = int.Parse(txt_tamanio2.Text);
filter.ApplyInPlace(difference);
//var sobl = new SobelEdgeDetector();
//sobl.ApplyInPlace(difference);
//erode image
var erode = new Erosion3x3();
for (int i = 0; i < int.Parse(txt_ers.Text); i++)
{
erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
}
// dilate remaining blobs
var dilate = new BinaryDilation3x3();
for (int i = 0; i < int.Parse(txt_dils.Text); i++)
{
dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
}
// put this image in the thresholded picturebox
thresholdedBox.Image = difference.Clone() as Bitmap;
// use this as a mask for the current frame
var mask = new ApplyMask(difference);
var maskedFrame = mask.Apply(frame);
// put this image in the masked picturebox
maskedBox.Image = maskedFrame.Clone() as Bitmap;
// now find all moving blobs
if (frameIndex % 10 == 0)
{
var counter = new BlobCounter();
counter.ProcessImage(difference);
// only keep blobs that:
// - do not overlap with known cars
// - do not overlap with other blobs
// - have crossed the middle of the frame
// - are at least 100 pixels tall
var blobs = counter.GetObjectsRectangles();
var newBlobs = from r in counter.GetObjectsRectangles()
where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r)) &&
!blobs.Any(b => b.IntersectsWith(r) && b != r) &&
r.Top >= 240 && r.Bottom <= 480 &&
r.Height >= int.Parse(txt_tamanio.Text)
select r;
// set up new camshift trackers for each detected blob
foreach (var rect in newBlobs)
{
trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
}
}
// now kill all car trackers that have expanded by too much
trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// and kill all trackers that have lived for 30 frames
//trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
trackers.RemoveAll(t => frameIndex - t.StartIndex > frames);
// let all remaining trackers process the current frame
var img = UnmanagedImage.FromManagedImage(maskedFrame);
trackers
.ForEach(t => t.Tracker.ProcessFrame(img));
// remember this frame for next iteration
previousFrame.Dispose();
previousFrame = frame.Clone() as Bitmap;
//escribir etiqueta para cada vehiculo
var outputFrame = frame.Clone() as Bitmap;
trackers
.FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
.ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// regresar frame procesado
frame = outputFrame;
}
else
{ // recordar para siguiente iteracion
previousFrame = frame.Clone() as Bitmap;
}
frameIndex++;
//if (previousFrame != null)
//{
// // find the thresholded euclidian difference between two subsequent frames
// ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
// threshold.OverlayImage = previousFrame;
// var difference = threshold.Apply(frame);
// // only keep big blobs
// var filter = new BlobsFiltering();
// filter.CoupledSizeFiltering = true;
// filter.MinHeight = 50;
// filter.MinWidth = 50;
// filter.ApplyInPlace(difference);
// // dilate remaining blobs
// var dilate = new BinaryDilation3x3();
// dilate.ApplyInPlace(difference);
// //dilate.ApplyInPlace(difference);
// //dilate.ApplyInPlace(difference);
// //dilate.ApplyInPlace(difference);
// // put this image in the thresholded picturebox
// thresholdedBox.Image = difference.Clone() as Bitmap;
// // use this as a mask for the current frame
// var mask = new ApplyMask(difference);
// var maskedFrame = mask.Apply(frame);
// // put this image in the masked picturebox
// maskedBox.Image = maskedFrame.Clone() as Bitmap;
// // now find all moving blobs
// if (frameIndex % 10 == 0)
// {
// var counter = new BlobCounter();
// counter.ProcessImage(difference);
// // only keep blobs that:
// // - do not overlap with known cars
// // - do not overlap with other blobs
// // - have crossed the middle of the frame
// // - are at least 100 pixels tall
// var blobs = counter.GetObjectsRectangles();
// var newBlobs = from r in counter.GetObjectsRectangles()
// where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r))
// && !blobs.Any(b => b.IntersectsWith(r) && b != r)
// && r.Top >= 240 && r.Bottom <= 480
// && r.Height >= 100
// select r;
// // set up new camshift trackers for each detected blob
// foreach (var rect in newBlobs)
// {
// trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
// }
// }
// // now kill all car trackers that have expanded by too much
// trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// // and kill all trackers that have lived for 30 frames
// trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
// // let all remaining trackers process the current frame
// var img = UnmanagedImage.FromManagedImage(maskedFrame);
// trackers
// .ForEach(t => t.Tracker.ProcessFrame(img));
// // remember this frame for next iteration
// previousFrame.Dispose();
// previousFrame = frame.Clone() as Bitmap;
// // draw labels on all tracked cars
// var outputFrame = frame.Clone() as Bitmap;
// trackers
// .FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
// .ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// // return the processed frame to the video
// frame = outputFrame;
//}
//// or else just remember this frame for next iteration
//else
// previousFrame = frame.Clone() as Bitmap;
//frameIndex++;
}
private void Cap_ImageGrabbed(object sender, EventArgs e)
{
try
{
Mat imagen = new Mat();
cap.Retrieve(imagen);
//pb_lprptzanalitica.Image = imagen.Bitmap;
Bitmap frame = new Bitmap(imagen.Bitmap);
//pb_ipcam.Image = frame.Clone() as Bitmap;
if (previousFrame != null)
{
// find the thresholded euclidian difference between two subsequent frames
//ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(40);
ThresholdedEuclideanDifference threshold = new ThresholdedEuclideanDifference(thr);
threshold.OverlayImage = previousFrame;
var difference = threshold.Apply(frame.Clone() as Bitmap);
// only keep big blobs
var filter = new BlobsFiltering();
filter.CoupledSizeFiltering = true;
filter.MinHeight = int.Parse(txt_tamanio2.Text);
filter.MinWidth = int.Parse(txt_tamanio2.Text);
filter.ApplyInPlace(difference);
//var sobl = new SobelEdgeDetector();
//sobl.ApplyInPlace(difference);
//erode image
var erode = new Erosion3x3();
for (int i = 0; i < int.Parse(txt_ers.Text); i++)
{
erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
//erode.ApplyInPlace(difference);
}
// dilate remaining blobs
var dilate = new BinaryDilation3x3();
for (int i = 0; i < int.Parse(txt_dils.Text); i++)
{
dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
//dilate.ApplyInPlace(difference);
}
// put this image in the thresholded picturebox
thresholdedBox.Image = difference.Clone() as Bitmap;
// use this as a mask for the current frame
var mask = new ApplyMask(difference);
var maskedFrame = mask.Apply(frame);
// put this image in the masked picturebox
maskedBox.Image = maskedFrame.Clone() as Bitmap;
// now find all moving blobs
if (frameIndex % 10 == 0)
{
var counter = new BlobCounter();
counter.ProcessImage(difference);
// only keep blobs that:
// - do not overlap with known cars
// - do not overlap with other blobs
// - have crossed the middle of the frame
// - are at least 100 pixels tall
var blobs = counter.GetObjectsRectangles();
var newBlobs = from r in counter.GetObjectsRectangles()
where !trackers.Any(t => t.Tracker.TrackingObject.Rectangle.IntersectsWith(r)) &&
!blobs.Any(b => b.IntersectsWith(r) && b != r) &&
r.Top >= 240 && r.Bottom <= 480 &&
r.Height >= int.Parse(txt_tamanio.Text)
select r;
// set up new camshift trackers for each detected blob
foreach (var rect in newBlobs)
{
trackers.Add(new TrackerType(rect, frameIndex, ++carIndex));
}
}
// now kill all car trackers that have expanded by too much
trackers.RemoveAll(t => t.Tracker.TrackingObject.Rectangle.Height > 360);
// and kill all trackers that have lived for 30 frames
//trackers.RemoveAll(t => frameIndex - t.StartIndex > 30);
trackers.RemoveAll(t => frameIndex - t.StartIndex > frames);
// let all remaining trackers process the current frame
var img = UnmanagedImage.FromManagedImage(maskedFrame);
trackers
.ForEach(t => t.Tracker.ProcessFrame(img));
// remember this frame for next iteration
previousFrame.Dispose();
previousFrame = frame.Clone() as Bitmap;
//escribir etiqueta para cada vehiculo
var outputFrame = frame.Clone() as Bitmap;
trackers
.FindAll(t => !t.Tracker.TrackingObject.IsEmpty)
.ForEach(t => DrawCarLabel(outputFrame, t.Tracker.TrackingObject.Rectangle, t.CarNumber));
// regresar frame procesado
frame = outputFrame;
//pb_ipcam.Image = outputFrame;
pb_lprptzanalitica.Image = outputFrame;
}
else
{ // recordar para siguiente iteracion
previousFrame = frame.Clone() as Bitmap;
}
frameIndex++;
}
catch (Exception)
{
MessageBox.Show("Error al decodificar video de PTZ, LPR o ANALITICA");
}
}