Develop Reference

How to get rid of unnecessary lines with emgu cv

I'm trying to detect contour of an ellipse-like water droplet with Emgu CV. I wrote code for contour detection:
public List<int> GetDiameters()
{
string inputFile = #"path.jpg";
Image<Bgr, byte> imageInput = new Image<Bgr, byte>(inputFile);
Image<Gray, byte> grayImage = imageInput.Convert<Gray, byte>();
Image<Gray, byte> bluredImage = grayImage;
CvInvoke.MedianBlur(grayImage, bluredImage, 9);
Image<Gray, byte> edgedImage = bluredImage;
CvInvoke.Canny(bluredImage, edgedImage, 50, 5);
Image<Gray, byte> closedImage = edgedImage;
Mat kernel = CvInvoke.GetStructuringElement(Emgu.CV.CvEnum.ElementShape.Ellipse, new System.Drawing.Size { Height = 100, Width = 250}, new System.Drawing.Point(-1, -1));
CvInvoke.MorphologyEx(edgedImage, closedImage, Emgu.CV.CvEnum.MorphOp.Close, kernel, new System.Drawing.Point(-1, -1), 0, Emgu.CV.CvEnum.BorderType.Replicate, new MCvScalar());
System.Drawing.Point(100, 250), 10000, Emgu.CV.CvEnum.BorderType.Default, new MCvScalar()
Image<Gray, byte> contoursImage = closedImage;
Image<Bgr, byte> imageOut = imageInput;
VectorOfVectorOfPoint rescontours1 = new VectorOfVectorOfPoint();
using (VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint())
{
CvInvoke.FindContours(contoursImage, contours, null, Emgu.CV.CvEnum.RetrType.List,
Emgu.CV.CvEnum.ChainApproxMethod.LinkRuns);
MCvScalar color = new MCvScalar(0, 0, 255);
int count = contours.Size;
for (int i = 0; i < count; i++)
{
using (VectorOfPoint contour = contours[i])
using (VectorOfPoint approxContour = new VectorOfPoint())
{
CvInvoke.ApproxPolyDP(contour, approxContour,
0.01 * CvInvoke.ArcLength(contour, true), true);
var area = CvInvoke.ContourArea(contour);
if (area > 0 && approxContour.Size > 10)
{
rescontours1.Push(approxContour);
}
CvInvoke.DrawContours(imageOut, rescontours1, -1, color, 2);
}
}
}
}
result so far:
I think there is a problem with approximation. How to get rid of internal lines and close external contour?

I might need some more information to exactly pinpoint your issue, but it might be something to do with your median blur. I would see if you are blurring enough that EmguCV things the blur is enough that you can canny edge detection. Another method that you could use is Dilate. Try Dialating your Canny edge detection and see if you get any better results.
EDIT
Here is the code below
public List<int> GetDiameters()
{
//List to hold output diameters
List<int> diametors = new List<int>();
//File path to where the image is located
string inputFile = #"C:\Users\jones\Desktop\Image Folder\water.JPG";
//Read in the image and store it as a mat object
Mat img = CvInvoke.Imread(inputFile, Emgu.CV.CvEnum.ImreadModes.AnyColor);
//Mat object that will hold the output of the gaussian blur
Mat gaussianBlur = new Mat();
//Blur the image
CvInvoke.GaussianBlur(img, gaussianBlur, new System.Drawing.Size(21, 21), 20, 20, Emgu.CV.CvEnum.BorderType.Default);
//Mat object that will hold the output of the canny
Mat canny = new Mat();
//Canny the image
CvInvoke.Canny(gaussianBlur, canny, 40, 40);
//Mat object that will hold the output of the dilate
Mat dilate = new Mat();
//Dilate the canny image
CvInvoke.Dilate(canny, dilate, null, new System.Drawing.Point(-1, -1), 6, Emgu.CV.CvEnum.BorderType.Default, new MCvScalar(0, 0, 0));
//Vector that will hold all found contours
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
//Find the contours and draw them on the image
CvInvoke.FindContours(dilate, contours, null, Emgu.CV.CvEnum.RetrType.External, Emgu.CV.CvEnum.ChainApproxMethod.ChainApproxSimple);
CvInvoke.DrawContours(img, contours, -1, new MCvScalar(255, 0, 0), 5, Emgu.CV.CvEnum.LineType.FourConnected);
//Variables to hold relevent info on what is the biggest contour
int biggest = 0;
int index = 0;
//Find the biggest contour
for (int i = 0; i < contours.Size; i++)
{
if (contours.Size > biggest)
{
biggest = contours.Size;
index = i;
}
}
//Once all contours have been looped over, add the biggest contour's index to the list
diametors.Add(index);
//Return the list
return diametors;
}
The first thing you do is blur the image.
Then you canny the image.
Then you dilate the image, as to make the final output contours more uniform.
Then you just find contours.
I know the final contours are a little bigger than the water droplet, but this is the best that I could come up with. You can probably fiddle around with some of the settings and the code above to make the result a little cleaner.

Count blob just once

Im working on a blob counting program that counts blob when it crosses a line.
I processed and detected the blob and got the centroid of the blob, i also have the centroid of the line. So I created an if statement that if blobcentroid.y >= linecentroid.y then count++ . But the problem is that the program freezes and keeps counting blob until a new blob is in the frame. Sometimes the blob is not counted at all. How do I fix this?
Code:
Image<Gray, byte> threshedimg = new Image<Gray, byte>(imgGrayColorFiltered.Bitmap);
Image<Bgr, byte> newimg = new Image<Bgr, byte>(threshedimg.Bitmap);
CvInvoke.Threshold(threshedimg, threshedimg, tthreshold.Value, 255, Emgu.CV.CvEnum.ThresholdType.Binary);
_blobDetector22.Detect(threshedimg, blobs1);
blobs1.FilterByArea(10, int.MaxValue);
float scale1 = (threshedimg.Width + threshedimg.Width) / 2.0f;
_tracker22.Update(blobs1, 0.01 * scale1, 5, 5);
Bitmap drawrect = new Bitmap(threshedimg.Bitmap);
foreach (var pair1 in _tracker22)
{
b1 = pair1.Value;
CvInvoke.Rectangle(newimg, b1.BoundingBox, new MCvScalar(255, 0, 0), 5);
CvInvoke.PutText(newimg, b1.Id.ToString(), new System.Drawing.Point((int)Math.Round(b1.Centroid.X), (int)Math.Round(b1.Centroid.Y)), FontFace.HersheyPlain, 3.0, new MCvScalar(0, 0, 255), 2);
}
pictureBox1.Image = newimg.Bitmap;
if (b1.Centroid.Y > linecentroid.Y)
{
increment++;
label1.Text = increment.ToString();
}

CvInvoke.MinAreaRect(contour) returns the wrong angle

I have a contour of a number plate and I want to check if it's tilted or not. I used CvInvoke.MinAreaRect(contour) but it always returns the angle == -90 even when the plate is obviously tilted, you can see the contour I draw in the picture below.
Does anyone know what happened and solution for my problem?
Here is the code:
Image<Gray, byte> gray = new Image<Gray, byte>("2.PNG");
Image<Gray, byte> adaptive_threshold_img = gray.ThresholdAdaptive(new Gray(255), AdaptiveThresholdType.GaussianC, ThresholdType.BinaryInv, 11, new Gray(2));
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
Mat hier = new Mat();
CvInvoke.FindContours(adaptive_threshold_img, contours, hier, RetrType.Tree, ChainApproxMethod.ChainApproxSimple);
double max_area = 0;
VectorOfPoint max_contour = new VectorOfPoint();
for (int i = 0; i < contours.Size; i++)
{
double temp = CvInvoke.ContourArea(contours[i]);
if (temp > max_area)
{
max_area = temp;
max_contour = contours[i];
}
}
VectorOfVectorOfPoint contour_to_draw = new VectorOfVectorOfPoint(max_contour);
CvInvoke.DrawContours(gray, contour_to_draw, 0, new MCvScalar(255), 2);
CvInvoke.Imshow("plate", gray);
RotatedRect plate_feature = CvInvoke.MinAreaRect(max_contour);
CvInvoke.WaitKey();
CvInvoke.DestroyAllWindows();

Try CvInvoke.threshold() instead of gray.ThresholdAdaptive(). Set proper threshold and you'll get better contour than before.

How to extract identified inner and outer contours using EmguCV?

I'm doing a project to process brain injuries using Image Processing. In order to improve its accuracy, I need to extract only the brain matter from the skull.
Using EmguCV I was able to identify the inner and outer contours (Blue and Dark blue). Is there anyway to extract these identified contours into another image?
Image<Gray, byte> grayImage = new Image<Gray, byte>(bitmap);
Image<Bgr, byte> color = new Image<Bgr, byte>(bitmap);
grayImage = grayImage.ThresholdBinary(new Gray(220), new Gray(255));
using (MemStorage storage = new MemStorage())
{
for (Contour<Point> contours = grayImage.FindContours(
Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE, Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_TREE, storage); contours != null; contours = contours.HNext)
{
Contour<Point> currentContour = contours.ApproxPoly(contours.Perimeter * 0.015, storage);
if (currentContour.BoundingRectangle.Width > 20)
{
CvInvoke.cvDrawContours(color, contours, new MCvScalar(100), new MCvScalar(255), -1, 2, Emgu.CV.CvEnum.LINE_TYPE.EIGHT_CONNECTED, new Point(0, 0));
}
}
}
EmguCV 2.2.2
Expected output:

Get position of objects using kinect and C#

I got a kinect mount in the ceiling pointing down to a table (that is roughly 2 to 3 meters of the kinect) and my objective is using the kinect depth stream, locate the objects and get their position to late send to unity. So for that i am using c sharp and opencv (emgu wrapper), i first use canny to get the edges and then use BoundingRect to create a box around the object.
The result is the as follows:
Original:
As you can see the stationary objects are no problem but the box around the hands (the first was a flyer on it) is to big and sometimes is even worse. Is there any other way (using opencv ) of getting the positions of the objects?
The objective is then to send the position and dimension (of the object) to unity (trough tcp/ip), so preferably the shapes have to squares or rectangles to easy manipulation on unity.
The code I have so far is:
Image<Bgr, Byte> grayImage = new Image<Bgr, Byte>("C:\\Users\\Pedro\\Desktop\\imgRva\\KinectSnapshot-03-48-01.png");
Image<Gray, Byte> gray = grayImage.Convert<Gray, Byte>().PyrDown().PyrUp();
CvInvoke.cvShowImage("texto", gray);
CvInvoke.cvWaitKey(0);
Image<Gray, Byte> bin = gray.ThresholdBinary(new Gray(40), new Gray(255));
Image<Gray, Byte> cannyEdges = bin.Canny(300, 300);
CvInvoke.cvShowImage("texto", cannyEdges);
CvInvoke.cvWaitKey(0);
Image<Gray, Byte> canny = new Image<Gray, byte>(cannyEdges.Size);
using (MemStorage storage = new MemStorage())
for (Contour<Point> contours = cannyEdges.FindContours(Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_NONE, Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_TREE, storage); contours != null; contours = contours.HNext)
{
CvInvoke.cvDrawContours(canny, contours, new MCvScalar(255), new MCvScalar(255), -1, 1, Emgu.CV.CvEnum.LINE_TYPE.EIGHT_CONNECTED, new Point(0, 0));
}
using (MemStorage store = new MemStorage())
for (Contour<Point> contours1 = cannyEdges.FindContours(Emgu.CV.CvEnum.CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_NONE, Emgu.CV.CvEnum.RETR_TYPE.CV_RETR_TREE, store); contours1 != null; contours1 = contours1.HNext)
{
Rectangle r = CvInvoke.cvBoundingRect(contours1, 1);
canny.Draw(r, new Gray(255), 1);
Debug.WriteLine(r.Location + " x " + r.Width + " y " + r.Height);
}
CvInvoke.cvShowImage("texto", canny);
CvInvoke.cvWaitKey(0);
Ty