I am trying the detect the pupil from a infrared image and calculate the center of the pupil.
In my setup, i used a camera sensitive to infrared light, and I added a visible light filter to the lens and two infrared LED around the camera.
However, the image I got is blur not so clear, maybe this caused by the low resolution of the camera, whose max is about 700x500.
In the processing, the first thing i did was to convert this RGB image to gray image, how ever the result is terrible. and it got nothing in the results.
int main()
{
//load image
cv::Mat src = cv::imread("11_13_2013_15_36_09.jpg");
cvNamedWindow("original");
cv::imshow("original", src);
cv::waitKey(10);
if (src.empty())
{
std::cout << "failed to find the image";
return -1;
}
// Invert the source image and convert to graysacle
cv::Mat gray;
cv::cvtColor(~src, gray, CV_BGR2GRAY);
cv::imshow("image1", gray);
cv::waitKey(10);
// Convert to binary image by thresholding it
cv::threshold(gray, gray, 220, 255, cv::THRESH_BINARY);
cv::imshow("image2", gray);
cv::waitKey(10);
// Find all contours
std::vector<std::vector<cv::Point>>contours;
cv::findContours(gray.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
// Fill holes in each contour
cv::drawContours(gray, contours, -1, CV_RGB(255, 255, 255), -1);
cv::imshow("image3", gray);
cv::waitKey(10);
for (int i = 0; i < contours.size(); i++)
{
double area = cv::contourArea(contours[i]);
cv::Rect rect = cv::boundingRect(contours[i]);
int radius = rect.width / 2;
// If controu is big enough and has round shape
// Then it is the pupil
if (area >= 800 &&
std::abs(1 - ((double)rect.width / (double)rect.height)) <= 0.3 &&
std::abs(1 - (area / (CV_PI * std::pow(radius, 2)))) <= 0.3)
{
cv::circle(src, cv::Point(rect.x + radius, rect.y + radius), radius, CV_RGB(255, 0, 0), 2);
}
}
cv::imshow("image", src);
cvWaitKey(0);
}
When the original image was converted, the gray image is terrible, does anyone know a better solution to this? I am completely new to this. for the rest of the code for finding the circle, if you have any comments, just tell me. and also i need to extra the position of the two glint (the light point) on the original image, does anyone has some idea?
thanks.
Try equalizing and filtering your source image before thresholding it ;)
Related
I have this code that basically reads each pixel of an image and redraws it with different shapes. All shapes will get faded in using a sin() wave.
Now I want to rotate every "Pixelshape" around its own axis (shapeMode(CENTER)) while they are faded in and the translate function gives me a headache in this complex way.
Here is the code so far:
void setup() {
size(1080, 1350);
shapeMode(CENTER);
img = loadImage("loremipsum.png");
…
}
void draw() {
background(123);
for (int gridX = 0; gridX < img.width; gridX++) {
for (int gridY = 0; gridY < img.height; gridY++) {
// grid position + tile size
float tileWidth = width / (float)img.width;
float tileHeight = height / (float)img.height;
float posX = tileWidth*gridX;
float posY = tileHeight*gridY;
// get current color
color c = img.pixels[gridY*img.width+gridX];
// greyscale conversion
int greyscale = round(red(c)*0.222+green(c)*0.707+blue(c)*0.071);
int gradientToIndex = round(map(greyscale, 0, 255, 0, shapeCount-1));
//FADEIN
float wave = map(sin(radians(frameCount*4)), -1, 1, 0, 2);
//translate(HEADACHE);
rotate(radians(wave));
shape(shapes[gradientToIndex], posX, posY, tileWidth * wave, tileHeight * wave);
}
}
I have tried many calculations but it just lets my sketch explode.
One that worked in another sketch where I tried basically the same but just in loop was (equivalent written):
translate(posX + tileWidth/2, posY + tileHeight/2);
I think I just don't get the matrix right? How can I translate them to its meant place?
Thank you very much #Rabbid76 – at first I just pasted in your idea and it went of crazy – then I added pushMatrix(); and popMatrix(); – turned out your translate(); code was in fact right!
Then I had to change the x and y location where every shape is drawn to 0,0,
And this is it! Now it works!
See the code here:
float wave = map(sin(radians(frameCount*4)), -1, 1, 0, 2);
pushMatrix();
translate(posX + tileWidth/2, posY + tileHeight/2);
rotate(radians(wave*180));
shape(shapes[gradientToIndex], 0, 0, tileWidth*wave , tileHeight*wave );
popMatrix();
PERFECT! Thank you so much!
rotate defines a rotation matrix and multiplies the current matrix by the rotation matrix. rotate therefore causes a rotation by (0, 0).
You have to center the rectangle around (0, 0), rotate it and move the rotated rectangle to the desired position with translate.
Since translate and rotate multiplies the current matrix by a new matrix, you must store and restore the matrix by pushMatrix() respectively popMatrix().
The center of a tile is (posX + tileWidth/2, posY + tileHeight/2):
pushMatrix();
translate(posX + tileWidth/2, posY + tileHeight/2);
rotate(radians(wave));
shape(shapes[gradientToIndex],
-tileWidth*wave/2, -tileHeight*wave/2,
tileWidth * wave, tileHeight * wave);
popMatrix();
I am developing a endless game, and want to take a Snapshot when the player Dies. I've almost done that using Texture2D. i have done Load Texture in image programmatically. but want to set border to the image. How can i do that.? how can i set border to that image at Run-time.?
This Code For Load Texture To the Image at Run-time when my player Dies.
void LoadImage(){
byte[] bytes = File.ReadAllBytes (Application.dataPath +"/GameOverScreenShot" + "/BirdDiedScreenShot.png");
Texture2D texture = new Texture2D (900, 900, TextureFormat.RGB24, false);
texture.filterMode = FilterMode.Trilinear;
texture.LoadImage (bytes);
Sprite sprite = Sprite.Create (texture, new Rect (0, 0, 700, 380), new Vector2 (0.5f, 0.0f), 1.0f);
imgObject.GetComponent<UnityEngine.UI.Image> ().sprite = sprite;
}
i want to Set Border to that image at Run-time. any one can help i really appreciate. thanks in Advance.
Do this after you load the image into the Texture2D variable and this will change the border of the image to whatever color you want.
//color should be a variable that holds the color of the border you want.
for (int i = 0; i< texture.width; i++){
texture.SetPixel(i, 0, color); //top border
texture.SetPixel(i, texture.height - 1, color); //bottom border
}
for (int j = 0; j < texture.height; j++){
texture.SetPixel(0, j, color); // left border
texture.SetPixel(texture.width - 1, j, color); //right border
}
texture.Apply();
This will replace any pixels on the edge of your original image so if you need those edge pixels you will need to look for another solution. Also, texture.Apply takes a while to run so if you need to constantly apply this border you may experience slowdown but you mentioned it is only when the player dies so this should not be an issue.
I have a problem whereby I want to estimate the gradient of the line on the contour. Please note that I dont need the pixel gradient but the rate of change of line.
If you see the attached image, you will see a binary image with green contour. I want to label each pixel based on the gradient of the pixel on the contour.
Why I need the gradient is because I want to compute the points where the gradient orientation changes from + to - or from - to +.
I cannot think of a good method, to estimate this point on the image. Could someone help me with suggestion on how I can estimate this points.
Here is a small program that computes the tangent at each contour pixel location in a very simple way (there exist other and probably better ways! the easy ones are: http://en.wikipedia.org/wiki/Finite_difference#Forward.2C_backward.2C_and_central_differences):
for a contour pixel c_{i} get the neighbors c_{i-1} and c_{i+1}
tangent direction at c_i is (c_{i-1} - c_{i+1}
So this is all on CONTOUR PIXELS but maybe you could so something similar if you compute the orthogonal to the full image pixel gradient... not sure about that ;)
here's the code:
int main()
{
cv::Mat input = cv::imread("../inputData/ContourTangentBin.png");
cv::Mat gray;
cv::cvtColor(input,gray,CV_BGR2GRAY);
// binarize
cv::Mat binary = gray > 100;
// find contours
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
findContours( binary.clone(), contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_NONE ); // CV_CHAIN_APPROX_NONE to get each single pixel of the contour!!
for( int i = 0; i< contours.size(); i++ )
{
std::vector<cv::Point> & cCont = contours[i];
std::vector<cv::Point2f> tangents;
if(cCont.size() < 3) continue;
// 1. compute tangent for first point
cv::Point2f cPoint = cCont.front();
cv::Point2f tangent = cCont.back() - cCont.at(1); // central tangent => you could use another method if you like to
tangents.push_back(tangent);
// display first tangent
cv::Mat tmpOut = input.clone();
cv::line(tmpOut, cPoint + 10*tangent, cPoint-10*tangent, cv::Scalar(0,0,255),1);
cv::imshow("tangent",tmpOut);
cv::waitKey(0);
for(unsigned int j=1; j<cCont.size(); ++j)
{
cPoint = cCont[j];
tangent = cCont[j-1] - cCont[(j+1)%cCont.size()]; // central tangent => you could use another method if you like to
tangents.push_back(tangent);
//display current tangent:
tmpOut = input.clone();
cv::line(tmpOut, cPoint + 10*tangent, cPoint-10*tangent, cv::Scalar(0,0,255),1);
cv::imshow("tangent",tmpOut);
cv::waitKey(0);
//if(cv::waitKey(0) == 's') cv::imwrite("../outputData/ContourTangentTangent.png", tmpOut);
}
// now there are all the tangent directions in "tangents", do whatever you like with them
}
for( int i = 0; i< contours.size(); i++ )
{
drawContours( input, contours, i, cv::Scalar(0,255,0), 1, 8, hierarchy, 0 );
}
cv::imshow("input", input);
cv::imshow("binary", binary);
cv::waitKey(0);
return 0;
}
I used this image:
and got outputs like:
in the result you get a vector with a 2D tangent information (line direction) for each pixel of that contour.
I am looking for advice from people having extensive experience with computer vision. I have a collection of ultrasonographic B&W images like the one below (without the stars and dotted line):
What I would like to do is detect the contour of a blood vessel (for example, the one highlighted by the yellow star). Of course my first step would be to define the ROI and maximize the contrast. But what would then be the best algorithm to use? Segmentation with the watershed algorithm? Something else?
I am little unsettled because of the image blur...
Edit:
As requested in the comments, here would be an example of source and result images:
Following is a simple approach to your problem, if I understood you correctly. My result is shown below.
And here is the code
int max_area_threshold = 10000;
int min_area_threshold = 1000;
float rational_threshold = 0.7;
cv::Mat img = cv::imread("sample.jpg", CV_8UC1);
cv::Mat img_binary;
//Create binary imae by tresholding
cv::threshold(img, img_binary, 25, 255, CV_THRESH_BINARY);
//Invert black-white
cv::bitwise_not(img_binary, img_binary);
//Eliminating small segments
cv::erode(img_binary, img_binary, cv::Mat(), cv::Point(-1, -1), 2, 1, 1);
cv::dilate(img_binary, img_binary, cv::Mat(), cv::Point(-1, -1), 1, 1, 1);
//Find contours
std::vector<std::vector<cv::Point>> contours;
std::vector<cv::Vec4i> hierarchy;
cv::findContours( img_binary, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE);
for( int i = 0; i< contours.size(); i++ )
{
if(contours[i].size() < 5)
continue;
//Fit ellipse to contour
cv::RotatedRect boundRect = cv::fitEllipse(contours[i]);
//Check the squareness of the bounding box
if(abs((boundRect.size.width / (float)boundRect.size.height)-1.0) > rational_threshold)
continue;
//Elliminate too big segments
if(boundRect.boundingRect().area() > max_area_threshold)
continue;
//Elliminate too small segments
if(boundRect.boundingRect().area() < min_area_threshold)
continue;
drawContours(img, contours, i, cv::Scalar(255), 0.2, 8, hierarchy, 0, cv::Point() );
}
cv::imwrite("result.jpg", img);
I hope it helps.
I have a piece of code here.
This is a camera capture application using OpenCV and Qt(for GUI).
void MainWindow::on_pushButton_clicked()
{
cv::VideoCapture cap(0);
if(!cap.isOpened()) return;
//namedWindow("edges",1);
QVector<QRgb> colorTable;
for (int i = 0; i < 256; i++) colorTable.push_back(qRgb(i, i, i));
QImage img;
img.setColorTable(colorTable);
for(;;)
{
cap >> image;
cvtColor(image, edges, CV_BGR2GRAY);
GaussianBlur(edges, edges, cv::Size(7,7), 1.5, 1.5);
Canny(edges, edges, 0, 30, 3);
//imshow("edges", edges);
if(cv::waitKey(30) >= 0) break;
// change color channel ordering
//cv::cvtColor(image,image,CV_BGR2RGB);
img = QImage((const unsigned char*)(edges.data),
image.cols,image.rows,QImage::Format_Indexed8);
// display on label
ui->label->setPixmap(QPixmap::fromImage(img,Qt::AutoColor));
// resize the label to fit the image
ui->label->resize(ui->label->pixmap()->size());
}
}
Initially "edges" is displayed in red with green background.Then it switches to blue background. This switching is happening randomly.
How can I display white edges in a black background in a stable manner.
In short, add the img.setColorTable(colorTable); just before the // display on labelcomment.
For more details, you create your image and affect the color table at the begining of your code:
QImage img;
img.setColorTable(colorTable);
Then in the infinite loop, you are doing the following:
img = QImage((const unsigned char*)(edges.data), image.cols, image.rows, QImage::Format_Indexed8);
What happens is that you destroy the image created at the begining of your code, the color map for this new image is not set and thus uses the default resulting in a colored output.