iris-recognition

In my eye tracking project, the pupil center is jumping a lot and I don't see it as a fixed point. What should I do? My idea is comparing the pupil center and pupil in 2 frames with a threshold but it doesn't help the problem. Another point is camera noise. What should I do to reduce the noises? I used the starburst algorithm . Starburst : A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. Eye trackers come with 2 types of noise/errors: variable and systematic error. Variable noise is basically the dispersion around the gazed target and the

I am trying to detect the eyes' irises but HoughCircles returns 0 circles. The input image(eyes) is: Then I made the following things with this image: cvtColor(eyes, gray, CV_BGR2GRAY); morphologyEx(gray, gray, 4,cv::getStructuringElement(cv::MORPH_RECT,cv::Size(3,3))); threshold(gray, gray, 0, 255, THRESH_OTSU); vector<Vec3f> circles; HoughCircles(gray, circles, CV_HOUGH_GRADIENT, 2, gray.rows/4); if (circles.size()) cout << "found" << endl; So the final gray image looks like this: I've found this question Using HoughCircles to detect and measure pupil and iris but it didn't help me despite

I am newbie to openCV, but I want to create iris recognition program. Although the system with webcam can detect the eyes, it cannot, however, detect the circular iris. I am using the Hough Circle Transformation. But in case iris in an image is not circular enough, system can't detect it. Any solution for it? the algorithm used is Hough Circle Transformation. IplImage *capturedImg = cvLoadImage("circle.jpg",1); IplImage *grayscaleImg = cvCreateImage(cvGetSize(capturedImg), 8, 1); cvCvtColor(capturedImg, grayscaleImg, CV_BGR2GRAY); // Gaussian filter for less noise cvSmooth(grayscaleImg,